Publications

2024

  1. A. Conev, R. Fasoulis, S. Hall-Swan, R. Ferreira, and L. E. Kavraki, “HLAEquity: Examining biases in pan-allele peptide-HLA binding predictors,” iScience, vol. 27, no. 1, Jan. 2024.
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  2. K. Muvvala, A. M. Wells, M. Lahijanian, L. E. Kvraki, and M. Y. Vardi, “Stochastic Games for Interactive Manipulation Domains,” in IEEE International Conference on Robotics and Automation, 2024. To Appear.
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  3. W. Thomason, Z. Kingston, and L. E. Kavraki, “Motions in Microseconds via Vectorized Sampling-Based Planning,” in IEEE International Conference on Robotics and Automation, 2024. To Appear.
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  4. C. Quintero-Peña, W. Thomason, Z. Kingston, A. Kyrillidis, and L. E. Kavraki, “Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty,” in IEEE International Conference on Robotics and Automation, 2024. To Appear.
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  5. K. Elimelech, Z. Kingston, W. Thomason, M. Y. Vardi, and L. E. Kavraki, “Accelerating long-horizon planning with affordance-directed dynamic grounding of abstract skills,” in IEEE International Conference on Robotics and Automation, 2024. To Appear.
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2023

  1. A. Conev, M. M. Rigo, D. Devaurs, A. F. Fonseca, H. Kalavadwala, M. V. de Freitas, C. Clementi, G. Zanatta, D. A. Antunes, and L. E. Kavraki, “EnGens: a computational framework for generation and analysis of representative protein conformational ensembles,” Briefings in Bioinformatics, p. bbad242, Jul. 2023.
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  2. K. Elimelech, L. E. Kavraki, and M. Y. Vardi, “Extracting generalizable skills from a single plan execution using abstraction-critical state detection,” in 2023 International Conference on Robotics and Automation (ICRA), 2023, pp. 5772–5778.
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  3. C. Quintero-Peña, Z. Kingston, T. Pan, R. Shome, A. Kyrillidis, and L. E. Kavraki, “Optimal Grasps and Placements for Task and Motion Planning in Clutter,” in 2023 International Conference on Robotics and Automation (ICRA), 2023, pp. 3707–3713.
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  4. S. Sobti, R. Shome, and L. E. Kavraki, “Efficient Inference of Temporal Task Specifications from Human Demonstrations using Experiment Design,” in 2023 International Conference on Robotics and Automation (ICRA), 2023, pp. 9764–9770.
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  5. Y. Lee, W. Thomason, Z. Kingston, and L. E. Kavraki, “Object Reconfiguration with Simulation-Derived Feasible Actions,” in 2023 International Conference on Robotics and Automation (ICRA), 2023, pp. 8104–8111.
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  6. Z. Kingston and L. E. Kavraki, “Scaling Multimodal Planning: Using Experience and Informing Discrete Search,” IEEE Transactions on Robotics, vol. 39, no. 1, pp. 128–146, Feb. 2023.
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  7. S. Hall-Swan, J. Slone, M. M. Rigo, D. A. Antunes, G. Lizée, and L. E. Kavraki, “PepSim: T-cell cross-reactivity prediction via comparison of peptide sequence and peptide-HLA structure,” Frontiers in Immunology, vol. 14, 2023.
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  8. F. Quintana, T. Treangen, and L. Kavraki, “Leveraging Large Language Models for Predicting Microbial Virulence from Protein Structure and Sequence,” in Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, New York, NY, USA, 2023.
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  9. R. Shome, Z. Kingston, and L. E. Kavraki, “Robots as AI Double Agents: Privacy in Motion Planning,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023. To Appear
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  10. E. E. Litsa, V. Chenthamarakshan, P. Das, and L. E. Kavraki, “An end-to-end deep learning framework for translating mass spectra to de-novo molecules,” Communications Chemistry, vol. 6, no. 1, p. 132, 2023.
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  11. S. B. Bayraktar, A. Orthey, Z. Kingston, M. Toussaint, and L. E. Kavraki, “Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces,” IEEE Robotics and Automation Letters, pp. 1–8, 2023.
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  12. K. Elimelech, L. E. Kavraki, and M. Y. Vardi, “Automatic Cross-domain Task Plan Transfer by Caching Abstract Skills,” in Algorithmic Foundations of Robotics XV, Cham, Switzerland, 2023, vol. 25, pp. 470–487.
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  13. K. Elimelech, L. E. Kavraki, and M. Y. Vardi, “Efficient task planning using abstract skills and dynamic road map matching,” in Robotics Research, Cham, Switzerland, 2023, vol. 27, pp. 487–503.
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  14. C. Quintero-Peña, P. Qian, N. Fontenot, H.-M. Chen, S. Hamlin, L. Kavraki, and V. Unhelkar, “Robotic Tutors for Nurse Training: Opportunities for HRI Researchers,” in 2023 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023.
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  15. J. L. Guo, L. E. Kavraki, and A. G. Mikos, “Editorial for Special Issue on Machine Learning in Tissue Engineering,” Tissue Engineering Part A, vol. 29, no. 1–2, pp. 1–1, 2023. PMID: 36399697
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  16. C. K. Verginis, D. V. Dimarogonas, and L. E. Kavraki, “KDF: Kinodynamic Motion Planning via Geometric Sampling-Based Algorithms and Funnel Control,” IEEE Transactions on Robotics, vol. 39, no. 2, pp. 978–997, 2023.
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2022

  1. Z. Kingston and L. E. Kavraki, “Robowflex: Robot Motion Planning with MoveIt Made Easy,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022, pp. 3108–3114.
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  2. K. Ren, L. E. Kavraki, and K. Hang, “Rearrangement-Based Manipulation via Kinodynamic Planning and Dynamic Planning Horizons,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022, pp. 1145–1152.
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  3. C. Chamzas, M. Lippi, M. C. Welle, A. Varava, L. E. Kavraki, and D. Kragic, “Comparing Reconstruction-and Contrastive-based Models for Visual Task Planning,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022, pp. 12550–12557.
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  4. K. R. Jackson, D. A. Antunes, A. H. Talukder, A. R. Maleki, K. Amagai, A. Salmon, A. S. Katailiha, Y. Chiu, R. Fasoulis, M. M. Rigo, J. R. Abella, B. D. Melendez, F. Li, Y. Sun, H. M. Sonnemann, V. Belousov, F. Frenkel, S. Justesen, A. Makaju, Y. Liu, D. Horn, D. Lopez-Ferrer, A. F. Huhmer, P. Hwu, J. Roszik, D. Hawke, L. E. Kavraki, and G. Lizée, “Charge-based interactions through peptide position 4 drive diversity of antigen presentation by human leukocyte antigen class I molecules,” PNAS Nexus, vol. 1, no. 3, Aug. 2022.
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  5. M. M. Rigo, R. Fasoulis, A. Conev, S. Hall-Swan, D. Amaral Antunes, and L. Kavraki, “SARS-Arena: Sequence and Structure-Guided Selection of Conserved Peptides from SARS-related Coronaviruses for Novel Vaccine Development,” Frontiers in Immunology, vol. 13, Jul. 2022.
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  6. Y. Lee, C. Chamzas, and L. E. Kavraki, “Adaptive Experience Sampling for Motion Planning using the Generator-Critic Framework,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 9437–9444, Jul. 2022.
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  7. A. Conev, D. Devaurs, M. M. Rigo, D. A. Antunes, and L. E. Kavraki, “3pHLA-score improves structure-based peptide-HLA binding affinity prediction,” Scientific Reports, vol. 12, no. 1, Jun. 2022.
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  8. S. Bansal, L. E. Kavraki, M. V. Vardi, and A. Wells, “Synthesis from Satisficing and Temporal Goals,” in Proceedings of the AAAI Conference on Artifical Intelligence, 2022, vol. 36, no. 9, pp. 9679–9686.
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  9. C. Quintero-Peña, C. Chamzas, Z. Sun, V. Unhelkar, and L. E. Kavraki, “Human-Guided Motion Planning in Partially Observable Environments,” in 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 7226–7232.
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  10. T. Pan, A. M. Wells, R. Shome, and L. E. Kavraki, “Failure is an option: Task and Motion Planning with Failing Executions,” in 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 1947–1953.
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  11. C. Chamzas, A. Cullen, A. Shrivastava, and L. E. Kavraki, “Learning to Retrieve Relevant Experiences for Motion Planning,” 2022 International Conference on Robotics and Automation (ICRA), pp. 7233–7240, May 2022.
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  12. C. Chamzas, C. Quintero-Peña, Z. Kingston, A. Orthey, D. Rakita, M. Gleicher, M. Toussaint, and L. E. Kavraki, “MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 882–889, Apr. 2022.
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  13. R. F. Tarabini, M. M. Rigo, A. Faustino Fonseca, F. Rubin, R. Bellé, L. E. Kavraki, T. C. Ferreto, D. Amaral Antunes, and A. P. D. de Souza, “Large-Scale Structure-Based Screening of Potential T Cell Cross-Reactivities Involving Peptide-Targets From BCG Vaccine and SARS-CoV-2,” Frontiers in Immunology, vol. 12, Jan. 2022.
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  14. C. Chamzas, F. Eweje, L. E. Kavraki, and E. L. Chaikof, “Human Health and Equity in an Age of Robotics and Intelligent Machines,” NAM Perspectives, 2022.
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2021

  1. R. Fasoulis, G. Paliouras, and L. E. Kavraki, “Graph representation learning for structural proteomics,” Emerging Topics in Life Sciences, Oct. 2021.
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  2. S. Sobti, R. Shome, S. Chaudhuri, and L. E. Kavraki, “A Sampling-based Motion Planning Framework for Complex Motor Actions,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 6928–6934.
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  3. Z. Kingston, C. Chamzas, and L. E. Kavraki, “Using Experience to Improve Constrained Planning on Foliations for Multi-Modal Problems,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 6922–6927.
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  4. Y. Wang, A. A. R. Newaz, J. D. Hernández, S. Chaudhuri, and L. E. Kavraki, “Online Partial Conditional Plan Synthesis for POMDPs With Safe-Reachability Objectives: Methods and Experiments,” IEEE Transactions on Automation Science and Engineering, vol. 18, pp. 932–945, Jul. 2021.
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  5. A. M. Wells, Z. Kingston, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Finite-Horizon Synthesis for Probabilistic Manipulation Domains,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2021, pp. 6336–6342.
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  6. R. Shome and L. E. Kavraki, “Asymptotically Optimal Kinodynamic Planning Using Bundles of Edges,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 9988–9994.
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  7. C. Quintero-Peña, A. Kyrillidis, and L. E. Kavraki, “Robust Optimization-based Motion Planning for high-DOF Robots under Sensing Uncertainty,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 9724–9730.
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  8. C. Chamzas, Z. Kingston, C. Quintero-Peña, A. Shrivastava, and L. E. Kavraki, “Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2021, pp. 1283–1289. (Top-4 finalist for best paper in Cognitive Robotics)
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  9. E. Pairet, C. Chamzas, Y. R. Petillot, and L. E. Kavraki, “Path Planning for Manipulation Using Experience-Driven Random Trees,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 3295–3302, Apr. 2021.
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  10. T. Pan, A. M. Wells, R. Shome, and L. E. Kavraki, “A General Task and Motion Planning Framework For Multiple Manipulators,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 3168–3174.
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  11. M. Moll, C. Chamzas, Z. Kingston, and L. E. Kavraki, “HyperPlan: A Framework for Motion Planning Algorithm Selection and Parameter Optimization,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, 2021, pp. 2511–2518.
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  12. E. E. Litsa, P. Das, and L. E. Kavraki, “Machine learning models in the prediction of drug metabolism: challenges and future perspectives,” Expert Opinion on Drug Metabolism & Toxicology, vol. 0, no. 0, pp. 1–3, 2021. PMID: 34706606
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  13. R. S. Rokosh, W. C. Lewis II, E. L. Chaikof, and L. E. Kavraki, “How Should We Prepare for the Post-Pandemic World of Telehealth and Digital Medicine?,” NAM Perspectives, 2021.
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  14. S. Hall-Swan, D. Devaurs, M. M. Rigo, D. A. Antunes, L. E. Kavraki, and G. Zanatta, “DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins,” Computers in Biology and Medicine, vol. 139, p. 104943, 2021.
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  15. K. Daniilidis, L. Guibas, L. Kavraki, P. Koumoutsakos, K. Kyriakopoulos, J. Lygeros, G. J. Pappas, M. Triantafyllou, and P. Tsiotras, “Robotics in the AI era: A vision for a Hellenic Robotics Initiative,” Foundations and Trends in Robotics, vol. 9, no. 3, pp. 201–265, 2021.
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2020

  1. C. Chamzas, M. Lippi, M. C. Welle, A. Varava, A. Marino, L. E. Kavraki, and D. Kragic, “State Representations in Robotics: Identifying Relevant Factors of Variation using Weak Supervision,” in NeurIPS, 3rd Robot Learning Workshop: Grounding Machine Learning Development in the Real World, 2020.
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  2. A. M. Wells, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “LTLf Synthesis on Probabilistic Systems,” Electronic Proceedings in Theoretical Computer Science, vol. 326, pp. 166–181, Sep. 2020.
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  3. E. E. Litsa, P. Das, and L. E. Kavraki, “Prediction of drug metabolites using neural machine translation,” Chemical Science, no. 11, pp. 12777–12788, Sep. 2020.
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  4. D. Devaurs, D. A. Antunes, and L. E. Kavraki, “Computational analysis of complement inhibitor compstatin using molecular dynamics,” Journal of Molecular Modeling, vol. 26, no. 231, Aug. 2020.
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  5. D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, pp. 623–636, Jul. 2020. PMID: 32667823, PMCID: 7397777
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  6. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “Large-scale structure-based prediction of stable peptide binding to Class I HLAs using random forests,” Frontiers in Immunology, vol. 11, no. 1583, Jul. 2020. PMID: 32793224, PMCID: PMC7387700
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  7. S. D. Butler, M. Moll, and L. E. Kavraki, “A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints,” in Proceedings of Algorithmic Foundations of Robotics XII, 2020, vol. 13, pp. 368–383.
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  8. R. Luna, M. Moll, J. M. Badger, and L. E. Kavraki, “A Scalable Motion Planner for High-Dimensional Kinematic Systems,” International Journal of Robotics Research, vol. 39, no. 4, pp. 361–388, Apr. 2020.
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  9. J. D. Hernández, S. Sobti, A. Sciola, M. Moll, and L. E. Kavraki, “Increasing Robot Autonomy via Motion Planning and an Augmented Reality Interface,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1017–1023, Apr. 2020.
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  10. S. M. Kim, M. I. Peña, M. Moll, G. N. Bennett, and L. E. Kavraki, “Improving the organization and interactivity of metabolic pathfinding with precomputed pathways,” BMC Bioinformatics, vol. 21, no. 1, p. 13, Jan. 2020. PMID: 31924164, PMCID: PMC6954563
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  11. O. Kravchenko, A. Varava, F. T. Pokorny, D. Devaurs, L. E. Kavraki, and D. Kragic, “A Robotics-Inspired Screening Algorithm for Molecular Caging Prediction,” Journal of Chemical Information and Modeling, vol. 60, no. 3, pp. 1302–1316, 2020. PMCID: PMC7307881
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  12. T. Arns, D. A. Antunes, J. R. Abella, M. M. Rigo, L. E. Kavraki, S. Giuliatti, and E. A. Donadi, “Structural Modeling and Molecular Dynamics of the Immune Checkpoint Molecule HLA-G,” Frontiers in Immunology, vol. 11, p. 2882, 2020. PMCID: PMC7677236
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  13. T. Pan, C. K. Verginis, A. M. Wells, L. E. Kavraki, and D. V. Dimarogonas, “Augmenting Control Policies with Motion Planning for Robust and Safe Multi-robot Navigation,” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 6975–6981, 2020.
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  14. A. Conev, E. Litsa, M. Perez, M. Diba, A. Mikos, and L. E. Kavraki, “Machine Learning Guided 3D Printing of Tissue Engineering Scaffolds,” Tissue Engineering Part A, vol. 26, no. 23-24, pp. 1359–1368, 2020.
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  15. Z. Kingston, A. M. Wells, M. Moll, and L. E. Kavraki, “Informing Multi-Modal Planning with Synergistic Discrete Leads,” in IEEE International Conference on Robotics and Automation, 2020, pp. 3199–3205.
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  16. J. R. Abella, D. Antunes, K. Jackson, G. Lizée, C. Clementi, and L. E. Kavraki, “Markov state modeling reveals alternative unbinding pathways for peptide–MHC complexes,” Proceedings of the National Academy of Sciences, vol. 117, no. 48, pp. 30610–30618, 2020.
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2019

  1. W. C. Lewis II, M. Moll, and L. E. Kavraki, “How Much Do Unstated Problem Constraints Limit Deep Robotic Reinforcement Learning?,” Rice University, Sep. 2019.
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  2. D. Devaurs, D. A. Antunes, S. Hall-Swan, N. Mitchell, M. Moll, G. Lizée, and L. E. Kavraki, “Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins,” BMC Molecular and Cell Biology, vol. 20, no. 1, p. 42, Sep. 2019. PMID: 31488048, PMCID: PMC6729087
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  3. E. Vidal Garcia, M. Moll, N. Palomeras, J. D. Hernández, M. Carreras, and L. E. Kavraki, “Online Multilayered Motion Planning with Dynamic Constraints for Autonomous Underwater Vehicles,” in IEEE International Conference on Robotics and Automation, 2019, pp. 8936–8942. (Top-3 finalist for best student paper award)
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  4. J. D. Hernández, M. Moll, and L. E. Kavraki, “Lazy Evaluation of Goal Specifications Guided by Motion Planning,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2019, pp. 944–950.
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  5. K. He, A. M. Wells, L. E. Kavraki, and M. Y. Vardi, “Efficient Symbolic Reactive Synthesis for Finite-Horizon Tasks,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2019, pp. 8993–8999. (Best paper award in Cognitive Robotics)
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  6. C. Chamzas, A. Shrivastava, and L. E. Kavraki, “Using Local Experiences for Global Motion Planning,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2019, pp. 8606–8612.
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  7. A. M. Wells, N. T. Dantam, A. Shrivastava, and L. E. Kavraki, “Learning Feasibility for Task and Motion Planning in Tabletop Environments,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1255–1262, Apr. 2019. PMID: 31058229, PMCID: PMC6491048
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  8. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Point-Based Policy Synthesis for POMDPs with Boolean and Quantitative Objectives,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1860–1867, Apr. 2019.
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  9. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Automated Abstraction of Manipulation Domains for Cost-Based Reactive Synthesis,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 285–292, Apr. 2019.
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  10. E. E. Litsa, M. I. Pena, M. Moll, G. Giannakopoulos, G. N. Bennett, and L. E. Kavraki, “Machine Learning Guided Atom Mapping of Metabolic Reactions,” Journal of Chemical Information and Modeling, vol. 59, no. 3, pp. 1121–1135, 2019. PMID: 30500191
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  11. Z. Kingston, M. Moll, and L. E. Kavraki, “Exploring Implicit Spaces for Constrained Sampling-Based Planning,” International Journal of Robotics Research, vol. 38, no. 10-11, pp. 1151–1178, 2019.
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  12. J. D. Hernández, E. Vidal, M. Moll, N. Palomeras, M. Carreras, and L. E. Kavraki, “Online Motion Planning for Unexplored Underwater Environments using Autonomous Underwater Vehicles,” Journal of Field Robotics, vol. 36, no. 2, pp. 370–396, 2019.
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  13. D. A. Antunes, J. R. Abella, D. Devaurs, M. M. Rigo, and L. E. Kavraki, “Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes,” Current Topics in Medicinal Chemistry, vol. 19, no. 1, 2019. PMID: 30582480, PMCID: PMC6361695
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  14. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations,” Molecules, vol. 24, no. 5, p. 881, 2019. PMID: 30832312, PMCID: PMC6429480
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2018

  1. E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative comparison of adaptive sampling methods for protein dynamics,” The Journal of Chemical Physics, vol. 149, no. 24, p. 244119, Dec. 2018. PMID: 30599712
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  2. F. Lagriffoul, N. Dantam, C. Garrett, A. Akbari, S. Srivastava, and L. E. Kavraki, “Platform-Independent Benchmarks for Task and Motion Planning,” IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3765–3772, Oct. 2018.
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  3. N. T. Dantam, S. Chaudhuri, and L. E. Kavraki, “The Task Motion Kit,” Robotics and Automation Magazine, vol. 25, no. 3, pp. 61–70, Sep. 2018.
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  4. Z. K. Kingston, M. Moll, and L. E. Kavraki, “Sampling-Based Methods for Motion Planning with Constraints,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, pp. 159–185, May 2018.
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  5. Muhayyuddin, M. Moll, L. E. Kavraki, and J. Rosell, “Randomized Physics-based Motion Planning for Grasping in Cluttered and Uncertain Environments,” IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 712–719, Apr. 2018.
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  6. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Online Partial Conditional Plan Synthesis for POMDPs with Safe-Reachability Objectives,” in Workshop on the Algorithmic Foundations of Robotics, 2018.
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  7. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Bounded Policy Synthesis for POMDPs with Safe-Reachability Objectives,” in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, Sweden, 2018, pp. 238–246.
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  8. D. Devaurs, M. Papanastasiou, D. A. Antunes, J. R. Abella, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Native state of complement protein C3d analysed via hydrogen exchange and conformational sampling,” International Journal of Computational Biology and Drug Design, vol. 11, no. 1/2, pp. 90–113, 2018. PMID: 30700993, PMCID: PMC6349257
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  9. D. Devaurs, D. A. Antunes, and L. E. Kavraki, “Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data,” International Journal of Molecular Sciences, vol. 19, no. 11, p. 3406, 2018. PMID: 30384411, PMCID: PMC6280153
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  10. N. T. Dantam, Z. K. Kingston, S. Chaudhuri, and L. E. Kavraki, “An Incremental Constraint-Based Framework for Task and Motion Planning,” International Journal of Robotics Research, vol. 37, no. 10, pp. 1134-1151. (Invited Article), 2018.
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  11. D. A. Antunes, D. Devaurs, M. Moll, G. Lizée, and L. E. Kavraki, “General prediction of peptide-MHC binding modes using incremental docking: A proof of concept,” Scientific Reports, vol. 8, p. 4327, 2018. PMCID: PMC5847594, PMID: 29531253
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  12. J. R. Abella, M. Moll, and L. E. Kavraki, “Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods,” Journal of Computational Biology, vol. 25, no. 1, pp. 3–20, 2018. PMID: 29035572, PMCID: PMC5756939
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2017

  1. D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach,” Cancer Research, vol. 77, no. 21, pp. 55–57, Nov. 2017. PMCID: PMC5679007, PMID: 29092940
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  2. S. M. Kim, M. I. Peña, M. Moll, G. N. Bennett, and L. E. Kavraki, “A Review of Parameters and Heuristics for Guiding Metabolic Pathfinding,” Journal of Cheminformatics, vol. 9, no. 1, p. 51, Sep. 2017. PMCID: PMC5602787, PMID: 29086092
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  3. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Reactive Synthesis For Finite Tasks Under Resource Constraints,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, 2017, pp. 5326–5332.
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  4. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Defining low-dimensional projections to guide protein conformational sampling,” Journal of Computational Biology, vol. 24, no. 1, pp. 79–89, 2017. PMID: 27892695
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  5. Z. Kingston, M. Moll, and L. E. Kavraki, “Decoupling Constraints from Sampling-Based Planners,” in Proceedings of the International Symposium of Robotics Research, Puerto Varas, Chile, 2017.
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  6. D. Halperin, L. E. Kavraki, and K. Solovey, “Robotics,” in Handbook of Discrete and Computational Geometry, J. E. Goodman, J. O’Rourke, and C. D. Tóth, Eds. Boca Raton, NY: CRC Press, 2017.
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  7. D. Devaurs, D. A. Antunes, M. Papanastasiou, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Coarse-grained conformational sampling of protein structure improves the fit to experimental hydrogen-exchange data,” Frontiers in Molecular Biosciences, vol. 4, no. 13, 2017. PMCID: PMC5344923, PMID: 28344973
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  8. W. Baker, Z. Kingston, M. Moll, J. Badger, and L. E. Kavraki, “Robonaut 2 and You: Specifying and Executing Complex Operations,” in Proceedings of the IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Austin, TX, 2017.
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  9. D. A. Antunes, M. M. Rigo, M. V. Freitas, M. M. FA, M. Sinigaglia, G. Lizée, L. E. Kavraki, L. K. Selin, M. Cornberg, and G. F. Vieira, “Interpreting T-cell cross-reactivity through structure: implications for TCR-based cancer immunotherapy,” Front. Immunol., vol. 8, no. 1210, 2017. PMCID: PMC5632759, PMID: 29046675
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2016

  1. S. Butler, M. Moll, and L. E. Kavraki, “A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints,” in Proceedings of the Workshop on the Algorithmic Foundations of Robotics, 2016.
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  2. J. Bohg, M. Ciocarlie, J. Civera, and L. E. Kavraki, “Big Data in Robotics,” Big Data, vol. 4, no. 4, pp. 195–196, Dec. 2016. PMID: 27992266
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  3. N. T. Dantam, K. Bøndergaard, M. A. Johansson, T. Furuholm, and L. E. Kavraki, “Unix Philosophy and the Real World: Control Software for Humanoid Robots,” Frontiers in Robotics and Artificial Intelligence, vol. 3, Mar. 2016.
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  4. Y. Wang, N. T. Dantam, S. Chaudhuri, and L. E. Kavraki, “Task and Motion Policy Synthesis as Liveness Games,” in Proceedings of the International Conference on Automated Planning and Scheduling, 2016, pp. 536–540.
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  5. F. T. Pokorny, D. Kragic, L. E. Kavraki, and K. Goldberg, “High-Dimensional Winding-Augmented Motion Planning with 2D Topological Task Projections and Persistent Homology,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2016, pp. 24–31.
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  6. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” BMC Genomics, vol. 17 (Suppl. 4), p. 431, 2016. PMID: 27556159, PMCID: PMC5001202
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  7. M. Lahijanian, M. R. Maly, D. Fried, L. E. Kavraki, H. Kress-Gazit, and M. Y. Vardi, “Iterative Temporal Planning in Uncertain Environments with Partial Satisfaction Guarantees,” IEEE Transactions on Robotics, vol. 32, no. 3, pp. 583–599, 2016.
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  8. S. M. Kim, M. I. Peña, M. Moll, G. Giannakopoulos, G. N. Bennett, and L. E. Kavraki, “An Evaluation of Different Clustering Methods and Distance Measures Used for Grouping Metabolic Pathways,” in 2016 International Conference on Bioinformatics and Computational Biology. ISCA, 2016, pp. 115–122.
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  9. L. E. Kavraki and M. Moll, “Editorial: Special Issue on the 2014 ‘Robotics: Science & Systems’ Conference,” International Journal of Robotics Research, vol. 3–4, no. 1–3, 2016.
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  10. L. E. Kavraki and S. M. LaValle, “Motion Planning,” in Handbook of Robotics, 2nd Edition, Springer, 2016. (http://www.bookmetrix.com/detail_full/book/bf39ef83-36b6-4bac-b546-a86864c58e19#downloads)
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  11. J. D. Hernández, M. Moll, E. Vidal Garcia, M. Carreras, and L. E. Kavraki, “Planning Feasible and Safe Paths Online for Autonomous Underwater Vehicles in Unknown Environments,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016, pp. 1313–1320.
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  12. N. T. Dantam, Z. K. Kingston, S. Chaudhuri, and L. E. Kavraki, “Incremental Task and Motion Planning: A Constraint-Based Approach,” in Robotics: Science and Systems, 2016.
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2015

  1. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Improving protein conformational sampling by using guiding projections,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), 2015, pp. 1272–1279.
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  2. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2015, pp. 21–28.
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  3. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Towards Manipulation Planning with Temporal Logic Specifications,” in Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, 2015, pp. 346–352.
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  4. M. Lahijanian, S. Almagor, D. Fried, L. E. Kavraki, and M. Y. Vardi, “This Time the Robot Settles for a Cost: A Quantitative Approach to Temporal Logic Planning with Partial Satisfaction,” in Proceedings of The Twenty-Ninth AAAI Conference (AAAI-15), Austin, TX, 2015, pp. 3664–3671.
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  5. C. Voss, M. Moll, and L. E. Kavraki, “A Heuristic Approach to Finding Diverse Short Paths,” in IEEE International Conference on Robotics and Automation, Seattle, WA, 2015, pp. 4173–4179.
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  6. L. E. Kavraki, D. Hsu, and J. Buchli, Eds., Robotics Science and Systems XI. 2015.
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  7. M. Moll, I. A. Şucan, and L. E. Kavraki, “Benchmarking Motion Planning Algorithms: An Extensible Infrastructure for Analysis and Visualization,” IEEE Robotics & Automation Magazine (Special Issue on Replicable and Measurable Robotics Research), vol. 22, no. 3, pp. 96–102, 2015.
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  8. P. K. Mandal, P. Morlacchi, J. M. Knight, T. M. Link, G. R. Lee, R. Nurieva, D. Singh, A. Dhanik, L. E. Kavraki, D. B. Corry, J. E. Ladbury, and J. S. McMurray, “Targeting the Src homology 2 (SH2) domain of signal transducer and activator of transcription 6 (STAT6) with cell-permeable, phosphatase-stable phosphopeptide mimics potently inhibits Tyr641 phosphorylation and transcriptional activity,” Journal of Medicinal Chemistry, 2015. PMCID: PMC5109833, PMID: 26506089
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  9. Z. Kingston, N. Dantam, and L. E. Kavraki, “Kinematically constrained workspace control via linear optimization,” in Proceedings of the IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), 2015, pp. 758–764.
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  10. L. E. Kavraki and M. Likhachev, “Editorial: Special Issue on the 2014 ‘Robotics: Science & Systems’ Conference,” Autonomous Robots, vol. 39, no. 3, 2015.
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  11. D. K. Grady, M. Moll, and L. E. Kavraki, “Extending the Applicability of POMDP Solutions to Robotic Tasks,” IEEE Transactions on Robotics, vol. 31, no. 4, pp. 948–961, 2015.
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  12. D. A. Antunes, D. Devaurs, and L. E. Kavraki, “Understanding the challenges of protein flexibility in drug design,” Expert Opinion on Drug Discovery, vol. 10, no. 12, pp. 1301–1313, 2015. PMID: 26414598
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2014

  1. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Optimal and Efficient Stochastic Motion Planning in Partially-Known Environments,” in Proceedings of The Twenty-Eighth AAAI Conference on Artificial Intelligence, Quebec City, Canada, 2014, pp. 2549–2555.
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  2. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Fast Stochastic Motion Planning with Optimality Guarantees using Local Policy Reconfiguration,” in Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China, 2014, pp. 3013–3019.
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  3. M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “A Sampling-Based Strategy Planner for Nondeterministic Hybrid Systems,” in Proceedings of the International Conference on Robotics and Automation, Hong Kong, China, 2014, pp. 3005–3012.
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  4. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Asymptotically Optimal Stochastic Motion Planning with Temporal Goals,” in Proceedings of the Workshop on the Algorithmic Foundations of Robotics, Istanbul, Turkey, 2014.
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  5. Z. Wang, Z. Wang, M. Moll, P.-S. Huang, D. K. Grady, N. Nasrabadi, T. Huang, L. E. Kavraki, and M. Hasegawa-Johnson, “Active Planning, Sensing and Recognition Using a Resource-Constrained Discriminant POMDP,” in Proceedings of the IEEE/ISPRS Workshop on Multi-Sensor Fusion for Outdoor Dynamic Scene Understanding at CVPR, 2014.
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  6. D. Fox, L. E. Kavraki, and H. Kurniawati, Eds., Robotics Science and Systems X. 2014.
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  7. S. Nedunuri, S. Prabhu, M. Moll, S. Chaudhuri, and L. E. Kavraki, “SMT-Based Synthesis of Integrated Task and Motion Plans for Mobile Manipulation,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2014, pp. 655–662.
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2013

  1. D. K. Grady, M. Moll, and L. E. Kavraki, “Combining a POMDP Abstraction with Replanning to Solve Complex, Position-Dependent Sensing Tasks,” in Proceedings of the AAAI Fall Symposium, Arlington, Virginia, 2013.
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  2. R. Luna, I. A. Şucan, M. Moll, and L. E. Kavraki, “Anytime Solution Optimization for Sampling-Based Motion Planning,” in Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013, pp. 5053–5059.
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  3. D. K. Grady, M. Moll, and L. E. Kavraki, “Automated Model Approximation for Robotic Navigation with POMDPs,” in Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013, pp. 78–84.
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  4. M. R. Maly, M. Lahijanian, L. E. Kavraki, H. Kress-Gazit, and M. Y. Vardi, “Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments,” in ACM International Conference on Hybrid Systems: Computation and Control (HSCC), Philadelphia, PA, USA, 2013, pp. 353–362.
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  5. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Falsification of LTL safety properties in hybrid systems,” International Journal on Software Tools for Technology Transfer (STTT), vol. 15, no. 4, pp. 305–320, 2013.
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  6. M. Moll, J. Bordeaux, and L. E. Kavraki, “Software for Project-Based Learning of Robot Motion Planning,” Computer Science Education, Special Issue on Robotics in CS Education, vol. 23, no. 4, pp. 332–348, 2013.
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  7. B. Gipson, M. Moll, and L. E. Kavraki, “SIMS: A hybrid method for rapid conformational analysis,” PLOS ONE, vol. 8, no. 7, p. 68826, 2013. PMCID: PMC3720858, PMID: 23935893
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  8. B. Gipson, M. Moll, and L. E. Kavraki, “Resolution Independent Density Estimation for Motion Planning in High-Dimensional Spaces,” in IEEE International Conference on Robotics and Automation, 2013, pp. 2429–2435.
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  9. A. Dhanik, J. McMurray, and L. E. Kavraki, “DINC: A new AutoDock-based protocol for docking large ligands,” BMC Structural Biology, vol. 13, no. Suppl 1, p. 11, 2013. PMCID: PMC3952135, PMID: 24564952
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  10. J. Chyan, M. Moll, and L. E. Kavraki, “Improving the Prediction of Kinase Binding Affinity Using Homology Models,” in Proceedings of the Computational Structural Bioinformatics Workshop at the ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, Washington, DC, 2013.
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  11. D. H. Bryant, M. Moll, P. W. Finn, and L. E. Kavraki, “Combinatorial clustering of residue position subsets predicts inhibitor affinity across the human kinome,” PLoS Computational Biology, vol. 9, no. 6, p. 1003087, 2013. PMCID: PMC3675009, PMID: 23754939
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2012

  1. I. A. Şucan, M. Moll, and L. E. Kavraki, “The Open Motion Planning Library,” IEEE Robotics & Automation Magazine, vol. 19, pp. 72–82, Dec. 2012. http://ompl.kavrakilab.org
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  2. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Robot Target Verification with Reachability Constraints,” in IEEE International Symposium on Safety, Security, and Rescue Robotics, College Station, TX, 2012, pp. 1–6.
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  3. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Objective Sensor-Based Replanning for a Car-Like Robot,” in IEEE International Symposium on Safety, Security, and Rescue Robotics, College Station, TX, 2012, pp. 1–6.
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  4. M. R. Maly and L. E. Kavraki, “Low-Dimensional Projections for SyCLoP,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Algarve, Portugal, 2012, pp. 420–425.
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  5. I. A. Sucan and L. E. Kavraki, “Accounting for Uncertainty in Simultaneous Task and Motion Planning Using Task Motion Multigraphs,” in IEEE International Conference on Robotics and Automation, St. Paul, 2012, pp. 4822–4828.
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  6. B. Gipson, D. Hsu, L. E. Kavraki, and J.-C. Latombe, “Computational Models of Proteins Kinematics and Dynamics: Beyond Simulation,” Annual Reviews of Analytical Chemistry, vol. 5, pp. 273–291, Apr. 2012. PMCID: PMC4866812, PMID: 22524225
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  7. A. Shehu and L. E. Kavraki, “Modeling Structures and Motions of Loops in Protein Molecules,” Entropy, vol. 14, pp. 252–290, Feb. 2012.
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  8. K. E. Bekris, D. K. Grady, M. Moll, and L. E. Kavraki, “Safe Distributed Motion Coordination for Second-Order Systems With Different Planning Cycles,” International Journal of Robotics Research, vol. 31, no. 2, pp. 129–150, Feb. 2012.
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  9. I. A. Sucan and L. E. Kavraki, “A Sampling-Based Tree Planner for Systems With Complex Dynamics,” IEEE Transactions on Robotics, vol. 28, no. 1, pp. 116–131, 2012.
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  10. A. Dhanik, J. S. McMurray, and L. E. Kavraki, “Binding Modes of Peptidomimetics Designed to Inhibit STAT3,” PLoS ONE, vol. 7(12), p. 51603, 2012. PMCID: PMC3520966, PMID: 23251591
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  11. A. Dhanik, J. S. McMurray, and L. E. Kavraki, “AUTODOCK-based Incremental Docking Protocol to Improve Docking of Large Ligands,” in IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), Philadelphia, 2012, pp. 48–55.
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  12. A. Dhanik and L. E. Kavraki, “Protein-ligand interactions: computational docking,” Encyclopedia of Life Sciences, 2012.
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2011

  1. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “An Algorithm for Efficient Identification of Branched Metabolic Pathways,” Journal of Computational Biology, vol. 18, no. 11, pp. 1575–1597, Nov. 2011. PMID: 21999288
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  2. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Look Before You Leap: Predictive Sensing and Opportunistic Navigation,” in Workshop on Progress and Open Problems in Motion Planning at the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, 2011.
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  3. A. Bhatia, M. R. Maly, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Complex Goals,” Robotics Automation Magazine, IEEE, vol. 18, no. 3, pp. 55–64, Sep. 2011.
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  4. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Server and Tools for Substructure-Based Functional Annotation,” Bioinformatics, vol. 27, no. 15, pp. 2161–2162, Aug. 2011. PMID: 21659320
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  5. A. Dhanik, J. S. McMurray, and L. E. Kavraki, “On modeling peptidomimetics in complex with the SH2 domain of Stat3,” in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC ’11), Boston, Massachusetts, USA, 2011, pp. 3329–3332.
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  6. I. A. Sucan and L. E. Kavraki, “On the Advantages of Using Task Motion Multigraphs for Efficient Mobile Manipulation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, 2011, pp. 4621–4626.
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  7. I. A. Sucan and L. E. Kavraki, “Mobile Manipulation: Encoding Motion Planning Options Using Task Motion Multigraphs,” in IEEE International Conference on Robotics and Automation, Shanghai, China, 2011, pp. 5492–5498.
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  8. M. Moll, I. A. Sucan, J. Bordeaux, and L. E. Kavraki, “Teaching Motion Planning Concepts to Undergraduate Students,” in IEEE Workshop on Advanced Robotics and its Social Impacts, 2011.
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  9. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “Identifying Branched Metabolic Pathways by Merging Linear Metabolic Pathways,” 15th Annual International Conference on Research in Computational Molecular Biology (RECOMB), vol. 6577/2011, pp. 70–84, 2011.
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  10. D. K. Grady, K. E. Bekris, and L. E. Kavraki, “Asynchronous Distributed Motion Planning with Safety Guarantees under Second-Order Dynamics,” in Algorithmic Foundations of Robotics IX, Singapore, Singapore, 2011, vol. 68, pp. 53–70.
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2010

  1. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Algorithm for Substructure Matching,” BMC Bioinformatics, vol. 11, p. 555, Dec. 2010. PMCID: PMC2996407, PMID: 21070651
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  2. H. Stamati, C. Clementi, and L. E. Kavraki, “Application of nonlinear dimensionality reduction to characterize the conformational landscape of small peptides,” Proteins, vol. 78, no. 2, pp. 223–235, Jul. 2010. PMCID: PMC2795065, PMID: 19731366
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  3. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Dynamics by a Synergistic Combination of Layers of Planning,” IEEE Transactions on Robotics, vol. 26, no. 3, pp. 469–482, Jun. 2010.
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  4. A. Bhatia, L. E. Kavraki, and M. Y. Vardi, “Sampling-Based Motion Planning with Temporal Goals,” in IEEE International Conference on Robotics and Automation, Anchorage, Alaska, 2010, pp. 2689–2696.
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  5. I. A. Sucan and L. E. Kavraki, “On the Implementation of Single-Query Sampling-Based Motion Planners,” in IEEE International Conference on Robotics and Automation, Anchorage, Alaska, 2010, pp. 2005–2011.
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  6. M. Moll, J. Bordeaux, and L. E. Kavraki, “Teaching Robot Motion Planning,” Computers in Education (Special Issue on Novel Approaches to Robotics Education), vol. 20, no. 3, pp. 50–59, 2010.
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  7. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “Finding Metabolic Pathways Using Atom Tracking,” Bioinformatics, vol. 26, no. 12, pp. 1548–1555, 2010. PMID: 20421197, PMCID: PMC2881407
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  8. N. Haspel, M. Moll, M. L. Baker, W. Chiu, and L. E. Kavraki, “Tracing conformational changes in proteins,” BMC Structural Biology, vol. 10, no. Suppl. 1, p. 1, 2010. PMCID: PMC2873824, PMID: 20487508
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  9. D. H. Bryant, M. Moll, B. Y. Chen, V. Y. Fofanov, and L. E. Kavraki, “Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction,” BMC Bioinformatics, vol. 11, no. 242, p. 242, 2010. PMCID: PMC2885373, PMID: 20459833
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  10. A. Bhatia, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Hybrid Dynamics and Temporal Goals,” in IEEE Conference on Decision and Control, Atlanta, GA, 2010, pp. 1108–1115.
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2009

  1. I. A. Sucan and L. E. Kavraki, “On the Performance of Random Linear Projections for Sampling-Based Motion Planning,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, 2009, pp. 2434–2439.
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  2. R. B. Rusu, I. A. Sucan, B. P. Gerkey, S. Chitta, M. Beetz, and L. E. Kavraki, “Real-Time Perception-Guided Motion Planning for a Personal Robot,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, 2009, pp. 4245–4252.
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  3. I. A. Sucan and L. E. Kavraki, “Kinodynamic Motion Planning by Interior-Exterior Cell Exploration,” in Algorithmic Foundation of Robotics VIII (Proceedings of Workshop on the Algorithmic Foundations of Robotics), Guanajuato, Mexico, 2009, vol. 57, pp. 449–464.
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  4. A. Shehu, L. E. Kavraki, and C. Clementi, “Multiscale characterization of protein conformational ensembles,” Proteins, vol. 76, no. 4, pp. 837–851, 2009. PMCID: PMC3164158, PMID: 19280604
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  5. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Hybrid systems: from verification to falsification by combining motion planning and discrete search,” Formal Methods in System Design, vol. 34, pp. 157–182, 2009.
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  6. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Falsification of LTL Safety Properties in Hybrid Systems,” in Proceedings of the Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2009), York, UK, 2009.
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  7. A. P. Heath and L. E. Kavraki, “Computational Challenges in Systems Biology,” Computer Science Review, vol. 3, no. 1, pp. 1–17, 2009.
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  8. N. Haspel, M. Moll, M. L. Baker, W. Chiu, and L. E. Kavraki, “Tracing Conformational Changes in Proteins,” in IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), Washington, DC, 2009.
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  9. N. Haspel, B. Geisbrecht, J. D. Lambris, and L. E. Kavraki, “Multi-scale Characterization of the Energy Landscape of Proteins with Application to the C3d/Efb-C Complex,” Proteins: Structure, function and bioinformatics, vol. 78, no. 4, pp. 1004–1014, 2009. PMCID: PMC2827694, PMID: 19899169
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  10. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “Safe and Distributed Kinodynamic Replanning for Vehicular networks,” ACM/Springer Mobile Networks and Applications (MONET), vol. 14, no. 3, pp. 292–308, 2009.
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2008

  1. N. Haspel, D. Ricklin, B. Geisbrecht, J. D. Lambris, and L. E. Kavraki, “Electrostatic Contributions Drive the Interaction Between Staphylococcus aureus Protein Efb-C and its Complement Target C3d,” Protein Science, vol. 17(11), pp. 1894–1906, Nov. 2008. PMID: 18687868, PMCID: PMC2578803
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  2. K. I. Tsianos and L. E. Kavraki, “Replanning: A powerful planning strategy for hard kinodynamic problems,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, France, 2008, pp. 1667–1672.
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  3. D. Ricklin, S. K. Ricklin-Lichtsteiner, G. Sfyroera, H. Chen, A. Tzekou, P. Magotti, Y.-Q. Wu, B. L. Garcia, W. J. McWorther, N. Haspel, L. E. Kavraki, B. Geisbrecht, and J. D. Lambris, “Novel insights into target specificities and molecular mechanisms for two potent complement evasion proteins from Staphylococcus aureus.,” in XXII International Complement Workshop, Basel, Switzerland, 2008.
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  4. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning,” in Robotics: Science and Systems, Atlanta, Georgia, 2008, pp. 326–333.
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  5. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Impact of Workspace Decompositions on Discrete Search Leading Continuous Exploration (DSLX) Motion Planning,” in IEEE International Conference on Robotics and Automation, Pasadena, CA, 2008, pp. 3751–3756.
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  6. K. I. Tsianos, D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robot Algorithms,” in Algorithms and Theory of Computation Handbook, Second., vol. 2, Boca Raton, FL: CRC Press, 2008.
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  7. I. A. Sucan, J. F. Kruse, M. Yim, and L. E. Kavraki, “Reconfiguration for modular robots using kinodynamic motion planning,” in ASME – Dynamic Systems and Control, Ann Arbor, Michigan, USA, 2008.
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  8. I. A. Sucan, J. F. Kruse, M. Yim, and L. E. Kavraki, “Kinodynamic Motion Planning with Hardware Demonstrations,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, France, 2008, pp. 1661–1666.
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  9. A. Shehu, L. E. Kavraki, and C. Clementi, “Unfolding the Fold of Cyclic Cysteine-rich Peptides,” Protein Science, vol. 17, pp. 482–493, 2008. PMCID: PMC2248317, PMID: 18287281
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  10. M. Moll and L. E. Kavraki, “Matching of Structural Motifs Using Hashing on Residue Labels and Geometric Filtering for Protein Function Prediction,” in The Seventh Annual International Conference on Computational Systems Bioinformatics (CSB2008), 2008, pp. 157–168.
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  11. M. Moll and L. E. Kavraki, “LabelHash: A Flexible and Extensible Method for Matching Structural Motifs,” in Automated Function Prediction / BioSapiens meeting (AFP-BioSapiens), 2008. Available from Nature Precedings.
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  12. D. M. Kristensen, M. R. Ward, A. M. Lisewski, S. Edrin, B. Y. Chen, V. Y. Fofanov, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “Prediction of enzyme function based on 3D templates of evolutionarily important amino acids,” BMC Bioinformatics, vol. 9, 2008. PMCID: PMC2219985, PMID: 18190718
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  13. A. P. Heath, G. Balázsi, and L. E. Kavraki, “Bipolarity of the saccharomyces cerevisiae genome,” International Conference on Bioinformatics and Biomedical Engineering (iCBBE), pp. 330–333, 2008.
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  14. V. Y. Fofanov, B. Y. Chen, D. H. Bryant, M. Moll, O. Lichtarge, L. E. Kavraki, and M. Kimmel, “A Statistical Model to Correct Systematic Bias Introduced by Algorithmic Thresholds in Protein Structural Comparison Algorithms,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philadelphia, PA, 2008.
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2007

  1. M. Moll, D. Schwarz, and L. E. Kavraki, “Roadmap Methods for Protein Folding,” in Protein Structure Prediction: Methods and Protocols, Humana Press, 2007. PMID: 18075168
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  2. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “A Distributed Protocol for Safe Real-Time Planning of Communicating Vehicles with Second-Order Dynamics,” in First International Conference on Robot Communication and Coordination (ROBOCOMM 07), Athens, Greece, 2007.
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  3. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “A Decentralized Planner that Guarantees the Safety of Communicating Vehicles with Complex Dynamics that Replan Online,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, 2007.
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  4. K. I. Tsianos, I. A. Sucan, and L. E. Kavraki, “Sampling-based robot motion planning: Towards realistic applications,” Computer Science Review, vol. 1, pp. 2–11, Aug. 2007.
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  5. A. P. Heath, L. E. Kavraki, and C. Clementi, “From coarse-grain to all-atom: Toward multiscale analysis of protein landscapes,” Proteins: Structure, Function and Bioinformatics, vol. 68, no. 3, pp. 646–661, Aug. 2007. PMID: 17523187
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  6. K. E. Bekris and L. E. Kavraki, “Greedy but Safe Replanning under Kinodynamic Constraints,” in International Conference on Robotics and Automation, Rome, Italy, 2007, pp. 704–710.
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  7. A. Shehu, L. E. Kavraki, and C. Clementi, “On the Characterization of Protein Native State Ensembles,” Biophysical Journal, vol. 92, no. 5, pp. 1503–1511, 2007. PMCID: PMC1796840, PMID: 17158570
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  8. A. Shehu, C. Clementi, and L. E. Kavraki, “Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins,” Algorithmica, vol. 48, pp. 303–327, 2007.
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  9. D. Schwarz and L. E. Kavraki, “Protein-Ligand Interactions: Computational Docking,” in Encyclopedia of Life Sciences, Wiley, 2007, p. 4105.
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  10. E. Plaku, H. Stamati, C. Clementi, and L. E. Kavraki, “Fast and Reliable Analysis of Molecular Motion Using Proximity Relations and Dimensionality Reduction,” Proteins: Structure, Function, and Bioinformatics, vol. 67, no. 4, pp. 897–907, 2007. PMID: 17380507
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  11. E. Plaku and L. E. Kavraki, “Nonlinear Dimensionality Reduction Using Approximate Nearest Neighbors,” in SIAM International Conference on Data Mining (SDM), Minneapolis, Minnesota, 2007, pp. 3711–3716.
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  12. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “A Motion Planner for a Hybrid Robotic System with Kinodynamic Constraints,” in IEEE International Conference on Robotics and Automation (ICRA), Rome, Italy, 2007, pp. 692–697.
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  13. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Hybrid Systems: From Verification to Falsification,” in International Conference on Computer Aided Verification (CAV), Berlin, Germany, 2007, vol. 4590, pp. 468–481.
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  14. E. Plaku and L. E. Kavraki, “Distributed Computation of the KNN Graph for Large High-Dimensional Point Sets,” Journal of Parallel and Distributed Computing, vol. 67, no. 3, pp. 346–359, 2007. PMCID: PMC2764297, PMID: 19847318
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  15. E. Plaku, K. E. Bekris, and L. E. Kavraki, “OOPS for Motion Planning: An Online Open-source Programming System,” in IEEE International Conference on Robotics and Automation (ICRA), Rome, Italy, 2007, pp. 3711–3716.
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  16. B. Y. Chen, V. Y. Fofanov, D. H. Bryant, B. D. Dodson, D. M. Kristensen, A. M. Lisewski, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “The MASH Pipeline for Protein Function Prediction and an Algorithm for the Geometric Refinement of 3D Motifs,” Journal of Computational Biology, vol. 14, no. 6, pp. 791–816, 2007. PMID: 17691895
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  17. B. Y. Chen, D. H. Bryant, A. E. Cruess, J. H. Bylund, V. Y. Fofanov, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Composite Motifs Integrating Multiple Protein Structures Increase Sensitivity for Function Prediction,” in Computational Systems Bioinformatics Conference (CSB2007), 2007, pp. 343–355. PMID: 17951837
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  18. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, A. E. Cruess, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Cavity Scaling: Automated Refinement of Cavity-Aware Motifs in Protein Function Prediction,” Journal of Bioinformatics and Computational Biology, vol. 5, no. 2a, pp. 353–382, 2007. PMID: 17589966
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2006

  1. M. Moll and L. E. Kavraki, “Path Planning for Deformable Linear Objects,” IEEE Transactions on Robotics, vol. 22, no. 4, pp. 625–636, Aug. 2006.
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  2. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, A. E. Cruess, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Cavity-Aware Motifs Reduce False Positives in Protein Function Prediction,” in Systems Bioinformatics Conference (CSB), Stanford, CA, 2006, vol. 4, pp. 311–323. PMID: 17369649
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  3. P. Das, M. Moll, H. Stamati, L. E. Kavraki, and C. Clementi, “Low-dimensional Free-energy Landscapes of Protein-Folding Reactions by Nonlinear Dimensionality Reduction,” Proceedings of the National Academy of Sciences, vol. 103, no. 26, pp. 9885–9890, Jun. 2006. PMCID: PMC1502548, PMID: 16785435
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  4. K. E. Bekris, M. Glick, and L. E. Kavraki, “Evaluation of Algorithms for Bearing-Only SLAM,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), Orlando, FL, 2006, pp. 1937–1944.
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  5. B. Y. Chen, V. Y. Fofanov, D. H. Bryant, B. D. Dodson, D. M. Kristensen, A. M. Lisewski, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Geometric Sieving: Automated Distributed Optimization of 3D Motifs for Protein Function Prediction,” in Research in Computational Biology: 10th Annual International Conference (RECOMB), Venice, Italy, 2006. Published in Lecture Notes in Computer Science, A. Apostolico, C. Guerra, S. Istrail, P. Pevzner, M. Waterman (Eds), Springer, 3909/2006, 500-515
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  6. A. Shehu, C. Clementi, and L. E. Kavraki, “Modeling Protein Conformational Ensembles: From Missing Loops to Equilibrium Fluctuations,” Proteins: Structure, Function and Bioinformatics, vol. 65, no. 1, pp. 164–179, 2006. PMID: 16917941
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  7. E. Plaku and L. E. Kavraki, “Quantitative Analysis of Nearest Neighbors Search in High-Dimensional Sampling-based Motion Planning,” in Workshop on Algorithmic Foundations of Robotics (WAFR), New York, NY, 2006.
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  8. D. M. Kristensen, B. Y. Chen, V. Y. Fofanov, M. R. Ward, A. M. Lisewski, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “Recurrent Use of Evolutionary Importance for Functional Annotation of Proteins Based on Local Structural Similarity,” Protein Science, vol. 15, no. 6, pp. 1530–1536, 2006. PMCID: PMC2242527, PMID: 16672239
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  9. K. E. Bekris, A. A. Argyros, and L. E. Kavraki, “Exploiting Panoramic Vision for Angle-Based Robot Navigation,” in Lecture Notes in Computer Science, Vol. 33, Springer, 2006, pp. 229–251.
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2005

  1. A. M. Ladd and L. E. Kavraki, “Motion Planning in the Presence of Drift, Underactuation and Discrete System Changes,” in Robotics: Science and Systems I, Boston, MA, 2005, pp. 233–241.
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  2. H. Choset, W. Burgard, S. Hutchinson, G. Kantor, L. E. Kavraki, K. Lynch, and S. Thrun, Principles of Robot Motion: Theory, Algorithms, and Implementation. MIT Press, 2005.
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  3. E. Plaku and L. E. Kavraki, “Distributed Sampling-Based Roadmap of Trees for Large-Scale Motion Planning,” in IEEE International Conference on Robotics and Automation, Barcelona, Spain, 2005, pp. 3879–3884.
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  4. M. Moll and L. E. Kavraki, “Path Planning for Variable Resolution Minimal-Energy Curves of Constant Length,” in International Conference on Robotics and Automation, Barcelona, Spain, 2005, pp. 2143–2147.
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  5. A. M. Ladd, K. E. Bekris, A. Rudys, G. Marceau, L. E. Kavraki, and D. S. Wallach, “Robotics-Based Location Sensing using Wireless Ethernet (Invited),” Wireless Networks (The Journal of Mobile Communication, Computation and Information), vol. 11, no. 1-2, pp. 189–204, Jan. 2005.
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  6. M. Zhang, R. A. White, L. Wang, R. Goldman, L. E. Kavraki, and B. Hassett, “Improving Conformational Searches by Geometric Screening,” Bioinformatics, vol. 21, no. 5, pp. 624–630, 2005. PMID: 15479715
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  7. E. Plaku, K. E. Bekris, B. Y. Chen, A. M. Ladd, and L. E. Kavraki, “Sampling-Based Roadmap of Trees for Parallel Motion Planning,” IEEE Transactions on Robotics, vol. 21, no. 4, pp. 597–608, 2005.
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  8. A. M. Ladd and L. E. Kavraki, “Fast Tree-Based Exploration of State Space for Robots with Dynamics,” in Algorithmic Foundations of Robotics VI, 2005, pp. 297–312.
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  9. B. Y. Chen, V. Y. Fofanov, D. M. Kristensen, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Algorithms for Structural Comparison and Statistical Analysis of 3D Protein Motifs,” in Pacific Symposium on Biocomputing, Hawaii, USA, 2005. PMID: 15759639
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  10. A. A. Argyros, K. E. Bekris, S. C. Orphanoudakis, and L. E. Kavraki, “Robot Homing by Exploiting Panoramic Vision,” Autonomous Robots, vol. 19, no. 1, pp. 7–25, 2005.
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  11. M. Akinc, K. E. Bekris, B. Y. Chen, A. M. Ladd, E. Plaku, and L. E. Kavraki, “Probabilistic Roadmaps of Trees for Parallel Computation of Multiple Query Roadmaps,” in Robotic Research: The Eleventh International Symposium, 2005, pp. 80–89.
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2004

  1. A. Haeberlen, E. Flannery, A. M. Ladd, A. Rudys, D. S. Wallach, and L. E. Kavraki, “Practical Robust Localization over Large-Scale 802.11 Wireless Networks,” in Proceedings of the Tenth ACM International Conference on Mobile Computing and Networking (MOBICOM 2004), Philadelphia, PA, 2004, pp. 70–84.
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  2. A. M. Ladd, K. E. Bekris, A. Rudys, L. E. Kavraki, and D. S. Wallach, “On the Feasibility of Using Wireless Ethernet for Indoor Localization,” IEEE Transactions on Robotics and Automation, vol. 20, no. 3, pp. 555–559, Jun. 2004.
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  3. J. M. Phillips, N. Bedrosian, and L. E. Kavraki, “Guided Expansive Spaces Trees: A Search Strategy for Motion- and Cost-Constrained State Spaces,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), New Orleans, LA, 2004, pp. 3968–3973.
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  4. M. Moll and L. E. Kavraki, “Path Planning for Minimal Energy Curves of Constant Length,” in Proceedings of The IEEE International Conference on, New Orleans, LA, 2004, pp. 2826–2831.
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  5. A. M. Ladd and L. E. Kavraki, “Measure Theoretic Analysis of Probabilistic Path Planning,” IEEE Transactions on Robotics and Automation, vol. 20, no. 2, pp. 229–242, Apr. 2004.
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  6. K. E. Bekris, A. A. Argyros, and L. E. Kavraki, “Angle-Based Methods for Mobile Robot Navigation: Reaching the Entire Plane,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), New Orleans, LA, 2004, pp. 2373–2378.
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  7. M. Moll, D. Schwarz, A. P. Heath, and L. E. Kavraki, “On Flexible Docking Using Expansive Search,” Rice University, Houston, TX, 04-443, 2004.
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  8. A. M. Ladd and L. E. Kavraki, “Using Motion Planning for Knot Untangling,” International Journal of Robotics Research, vol. 23, no. 7-8, pp. 797–808, 2004.
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  9. A. M. Ladd and L. E. Kavraki, “Motion Planning for Knot Untangling,” in Algorithmic Foundations of Robotics V, Springer Tracks in Advanced Robotics, Springer Verlag, STAR 7, 2004, pp. 7–23.
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  10. D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robotics,” in Handbook of Discrete and Computational Geometry, Boca Raton, NY: CRC Press, 2004, pp. 1065–1094.
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2003

  1. K. E. Bekris, B. Y. Chen, A. M. Ladd, E. Plaku, and L. E. Kavraki, “Multiple Query Probabilistic Roadmap Planning Using Single Query Planning Primitives,” in 2003 IEEE/RJS International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, 2003, pp. 656–661.
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  2. J. M. Phillips, L. E. Kavraki, and N. Bedrosian, “Spacecraft Rendezvous and Docking With Real-Time Randomized Optimization,” in AIAA (American Institute of Aeronautics and Astronautics) Guidance, Navigation and Control Conference, Austin, TX, 2003.
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  3. J. M. Phillips, L. E. Kavraki, and N. Bedrosian, “Probabilistic Optimization Applied to Spacecraft Rendezvous and Docking,” in 13th American Astronomical Society/AIAA - Space Flight Mechanics Meeting, Puerto Rico, 2003.
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  4. H. Yao, D. M. Kristensen, I. Mihalek, M. Sowa, C. Shaw, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “An Accurate, Sensitive, and Scalable Method to Identify Functional Sites in Protein Structures,” Journal of Molecular Biology, vol. 326, no. 1, pp. 255–261, 2003. PMID: 12547207
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  5. M. L. Teodoro, G. N. Phillips Jr., and L. E. Kavraki, “Understanding Protein Flexibility through Dimensionality Reduction,” Journal of Computational Biology, vol. 10, no. 3-4, pp. 617–634, 2003. PMID: 12935348
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  6. M. L. Teodoro and L. E. Kavraki, “Conformational Flexibility Models for the Receptor in Structure Based Drug Design,” Current Pharmaceutical Design, vol. 9, pp. 1419–1431, 2003. PMID: 12871062
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2002

  1. M. Zhang and L. E. Kavraki, “Approximating Solutions of Molecular Inverse Kinematics Problems by Subdivision,” in The 24th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) and the Annual Meeting of the Biomedical Engineering Society (BMES), 2002, pp. 2182–2183.
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  2. A. M. Ladd, K. E. Bekris, G. Marceau, A. Rudys, L. E. Kavraki, and D. S. Wallach, “Using Wireless Ethernet for Localization,” in Proceedings of the 2002 IEEE/RJS International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Switzerland, 2002, vol. 1, pp. 402–408.
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  3. A. M. Ladd, K. E. Bekris, A. Rudys, G. Marceau, L. E. Kavraki, and D. S. Wallach, “Robotics-Based Location Sensing using Wireless Ethernet,” in Proceedings of the Eight ACM International Conference on Mobile Computing and Networking (MOBICOM 2002), Atlanta, GE, 2002, pp. 227–238.
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  4. M. L. Teodoro and L. E. Kavraki, “Pharmacology,” in Handbook of Data Mining and Knowledge Discovery, W. Klösgen and J. Żytkow, Eds. Oxford University Press, 2002, pp. 808–816.
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  5. J. M. Phillips, A. M. Ladd, and L. E. Kavraki, “Simulated Knot Tying,” in Proceedings of The 2002 IEEE International Conference on Robotics and Automation (ICRA 2002), Washington, DC, 2002, pp. 841–846.
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  6. A. M. Ladd and L. E. Kavraki, “Generalizing the Analysis of PRM,” in Proceedings of the 2002 IEEE International Conference on Robotics and Automation (ICRA 2002), Washington, DC, 2002, pp. 2120–2125.
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  7. M. Zhang and L. E. Kavraki, “Solving Molecular Inverse Kinematics Problems for Protein Folding and Drug Design,” in Currents in Computational Molecular Biology, 2002, pp. 214–215. Book includes short papers from The Sixth ACM International Conference on Research in Computational Biology (RECOMB 2002), Washington, DC, 2002
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  8. M. L. Teodoro, G. N. Phillips Jr., and L. E. Kavraki, “A Dimensionality Reduction Approach to Modeling Protein Flexibility,” in Proceedings of the 2002 ACM International Conference on Research in Computational Biology (RECOMB 2002), 2002, pp. 299–308.
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  9. M. Zhang and L. E. Kavraki, “A New Method for Fast and Accurate Derivation of Molecular Conformations,” Journal of Chemical Information and Computer Sciences, vol. 42, no. 1, pp. 64–70, 2002. PMID: 11855967
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  10. P. K. Agrawal, L. J. Guibas, H. Edelsbrunner, J. Erickson, M. Isard, S. Har-Peled, J. Hershberger, C. Jensen, L. E. Kavraki, P. Koehl, M. Lin, D. Manocha, D. Metaxas, B. Mirtich, D. Mount, and S. Muthukrishnan, “Algorithmic Issues in Modeling Motion,” ACM Computing Surveys, vol. 34, no. 4, pp. 550–572, 2002.
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2001

  1. A. Sudsang and L. E. Kavraki, “Part Orientation with a Force Field: Orienting Multiple Shapes using a Single Field,” in Proceedings of The 2001 IEEE/RJS International Conference on Intelligent Robots and Systems (IROS 2001), 2001, vol. 1, pp. 208–213.
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  2. M. L. Teodoro, G. N. Phillips Jr., and L. E. Kavraki, “Molecular Docking: A Problem with Thousands of Degrees of Freedom,” in Proc. of the 2001 IEEE International Conference on Robotics and Automation (ICRA 2001), Seoul, Korea, 2001, pp. 960–966.
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  3. A. Sudsang and L. E. Kavraki, “A Geometric Approach to Designing a Programmable Force Field with a Unique Stable Equilibrium for Parts in the Plane,” in Proceedings of The 2001 IEEE International Conference on Robotics and Automation (ICRA 2001), Seoul, Korea, 2001, vol. 2, pp. 1079–1085. This paper was a finalist for best conference paper award
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  4. O. Brock and L. E. Kavraki, “Decomposition-Based Motion Planning: A Framework for Real-Time Motion Planning in High-Dimensional Configuration Places,” in Proceedings of The 2001 IEEE International Conference on Robotics and Automation (ICRA), 2001, pp. 1469–1475.
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  5. M. Zhang and L. E. Kavraki, “Efficiently Maintaining Molecular Conformations Using Local Frames,” in Currents in Computational Molecular Biology, Montreal, Canada, 2001, pp. 97–98. Book includes short papers from The Fifth ACM International Conference on Research in Computational Biology (RECOMB), Montreal, Canada, 2001
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  6. J. Yakey, S. M. LaValle, and L. E. Kavraki, “Randomized Path Planning for Linkages with Closed Kinematics Chains,” IEEE Transactions on Robotics and Automation, vol. 17, no. 6, pp. 951–959, 2001.
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  7. F. Lamiraux and L. E. Kavraki, “Positioning Symmetric and Non-Symmetric Parts using Radial and Constant Force Fields,” in Robotics: New Directions, Natick, MA, 2001, pp. 37–50. Book contains the proceedings of the International Workshop on the Algorithmic Foundations of Robotics (WAFR), Dartmouth, March 2000
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  8. F. Lamiraux and L. E. Kavraki, “Positioning of Symmetric and Non-Symmetric Parts Using Radial and Constant Fields: Computation of All Equilibrium Configurations,” International Journal of Robotics Research, vol. 20, no. 8, pp. 635–659, 2001.
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  9. F. Lamiraux and L. E. Kavraki, “Planning Paths for Elastic Objects under Manipulation Constraints,” International Journal of Robotics Research, vol. 20, no. 3, pp. 188–208, 2001.
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  10. R. Bohlin and L. E. Kavraki, “A Randomized Algorithm for Robot Path Planning Based on Lazy Evaluation,” in Handbook on Randomized Computing, Kluwer Academic Publishers, 2001, pp. 221–249.
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2000

  1. C. Nielsen and L. E. Kavraki, “A Two-Level Fuzzy PRM for Manipulation Planning,” in Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2000, vol. 3, pp. 1716–1722.
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  2. J. Luo and L. E. Kavraki, “Part Assembly Using Static and Dynamic Force Fields,” in Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2000, vol. 2, pp. 1468–1474.
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  3. O. Brock and L. E. Kavraki, “Towards Real-Time Motion Planning in High Dimensional Spaces,” in Proceedings of The International Symposium on Robotics and Automation (ISRA), Monterey, Mexico, 2000.
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  4. M. L. Teodoro, G. N. Phillips Jr., and L. E. Kavraki, “Singular Value Decomposition of Protein Conformational Motions: Application to HIV-1 Protease,” in Currents in Computational Molecular Biology, Tokyo, Japan, 2000, pp. 198–199. Book includes short papers from The Forth ACM International Conference on Computational Biology (RECOMB), 2000
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  5. F. Lamiraux and L. E. Kavraki, “Positioning and Orienting a Class of Symmetric Parts Using a Combination of a Unit-Radial and a Constant Force Fields,” in Proceedings of The 2000 IEEE International Conference on Robotics and Automation (ICRA 2000), San Fransisco, CA, 2000, vol. 1, pp. 178–183.
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  6. T. Danner and L. E. Kavraki, “Randomized Planning for Short Inspection Paths,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), San Fransisco, CA, 2000, vol. 2, pp. 971–976.
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  7. R. Bohlin and L. E. Kavraki, “Path Planning Using Lazy PRM,” in Proceedings of the IEEE International Conference on Robotics and Automation, San Fransisco, CA, 2000, vol. 1, pp. 521–528.
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  8. E. Anshelevich, S. Owens, F. Lamiraux, and L. E. Kavraki, “Deformable Volumes in Path Planning Applications,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), San Fransisco, CA, 2000, vol. 3, pp. 2290–2295.
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  9. S. M. LaValle, P. W. Finn, L. E. Kavraki, and J.-C. Latombe, “A Randomized Kinematics-based Approach to Pharmacophore-Constrained Conformational Search and Database Screening,” Journal of Computational Chemistry, vol. 21, no. 9, pp. 731–747, 2000.
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  10. C. Holleman and L. E. Kavraki, “A Framework for Using the Workspace Medial Axis in PRM Planners,” in Proc. of the International Conference on Robotics and Automation (ICRA), San Fransisco, CA, 2000, vol. 2, pp. 1408–1413.
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  11. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “Part Orientation with One or Two Stable Equilibria Using Programmable Vector Fields,” IEEE Transactions on Robotics and Automation, vol. 16, no. 2, pp. 157–170, 2000.
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  12. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “A Distributed, Universal Device for Planar Parts Feeding: Unique Part Orientation in Programmable Vector Fields,” in Distributed Manipulation, Kluwer Academic Publishers, 2000, pp. 1–29.
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1999

  1. S. M. LaValle, J. Yakey, and L. E. Kavraki, “A Probabilistic Roadmap Approach for Systems with Closed Kinematic Chains,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), Detroit, MI, 1999, vol. 3, pp. 1671–1677.
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  2. F. Lamiraux and L. E. Kavraki, “Path Planning for Elastic Plates Under Manipulation,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), Detroit, MI, 1999, vol. 1, pp. 151–156.
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  3. S. M. LaValle, P. W. Finn, L. E. Kavraki, and J.-C. Latombe, “Efficient Database Screening for Rational Drug Design Using Pharmacophore-Constrained Conformational Search,” in The Third ACM International Conference on Computational Biology (RECOMB), Grenoble, France, 1999, pp. 250–259.
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  4. L. E. Kavraki, “Algorithms in Robotics: The Motion Planning Perspective,” in Frontiers of Engineering Publication, National Academy of Engineering, 1999, pp. 90–93.
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  5. D. Hsu, J.-C. Latombe, R. Motwani, and L. E. Kavraki, “Capturing the Connectivity of High-Dimensional Geometric Spaces by Parallelizable Random Sampling Techniques,” in Parallel and Distributed Processing, vol. 5, P. M. Pardalos and S. Rajasekaran, Eds. Springer, Boston, MA., 1999, pp. 159–182.
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  6. D. Halperin, L. E. Kavraki, J.-C. Latombe, and M. Attalah, “Robot Algorithms,” in Algorithms and Theory of Computation Handbook, Boca Raton, NY: CRC Press, 1999.
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  7. L. J. Guibas, C. Holleman, and L. E. Kavraki, “A Probabilistic Roadmap Planner for Flexible Objects with a Workspace Medial-Axis Based Sampling Approach,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyongju, Korea, 1999, vol. 1, pp. 254–260.
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  8. P. W. Finn and L. E. Kavraki, “Computational Approaches to Drug Design,” Algorithmica, vol. 25, pp. 347–371, 1999.
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  9. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “A Single Universal Force Field can Uniquely Orient Non-Symmetric Parts,” in Robotics Research: The 9th International Symposium, Springer, 1999, pp. 395–402.
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1998

  1. L. E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan, “Randomized Query Processing in Robot Path Planning,” Journal of Computer and System Sciences, vol. 57, no. 1, pp. 50–60, Aug. 1998.
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  2. L. E. Kavraki and J.-C. Latombe, “Probabilistic Roadmaps for Robot Path Planning,” in Practical Motion Planning in Robotics: Current Approaches and Future Directions, John Wiley, 1998, pp. 33–53.
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  3. L. E. Kavraki, F. Lamiraux, and C. Holleman, “Towards Planning for Elastic Objects,” in Robotics: The Algorithmic Perspective, Natick, MA, 1998, pp. 313–325. Proceedings of the Third Workshop on the Algorithmic Foundations of Robotics (WAFR), Houston, TX, 1998
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  4. L. E. Kavraki, M. N. Kolountzakis, and J.-C. Latombe, “Analysis of Probabilistic Roadmaps for Path Planning,” IEEE Transactions on Robotics and Automation, vol. 14, no. 1, pp. 166–171, 1998.
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  5. D. Hsu, L. E. Kavraki, J.-C. Latombe, R. Motwani, and S. Sorkin, “On Finding Narrow Passages with Probabilistic Roadmap Planners,” in Robotics: The algorithmic perspective, Natick, MA: A.K. Peters, 1998, pp. 141–153.
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  6. C. Holleman, L. E. Kavraki, and J. Warren, “Planning Paths for a Flexible Surface Patch,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), Leuven, Belgium, 1998, vol. 1, pp. 21–26.
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  7. P. W. Finn, L. E. Kavraki, J.-C. Latombe, C. Shelton, S. Venkat, and A. Yao, “RAPID: Randomized Pharmacophore Identification for drug design,” Computational Geometry: Theory and Applications, vol. 10, no. 4, pp. 263–272, 1998.
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  8. P. K. Agrawal, L. E. Kavraki, and M. Mason, Robotics: The Algorithmic Perspective. Natick MA: AK Peters, 1998.
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1997

  1. P. W. Finn, L. E. Kavraki, J.-C. Latombe, R. Motwani, and S. Venkat, “Search Techniques for Rational Drug Design,” in International Conference on Intelligent Information Systems, Grand Bahama, 1997, pp. 2–6.
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  2. B. Cook, L. E. Kavraki, and R. Motwani, “Efficient Clustering of Molecular Conformations,” in Second CGC Workshop on Computational Geometry, Duke University, 1997.
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  3. L. E. Kavraki, “Part Orientation with Programmable Vector Fields: Two Stable Equilibria for Most Parts,” in Proceedings of The International Conference on Robotics and Automation (ICRA), Albuquerque, NM, 1997, vol. 3, pp. 2446–2452.
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  4. L. E. Kavraki, “Geometry and the Discovery of New Ligands,” in Algorithms for Robotic Motion and Manipulation (WAFR 1996), A.K. Peters, 1997, pp. 435–448.
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  5. D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robotics,” in Handbook of Discrete and Computational Geometry, Boca Raton, NY: CRC Press, 1997, pp. 755–779.
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  6. P. W. Finn, L. E. Kavraki, J.-C. Latombe, R. Motwani, C. Shelton, S. Venkat, and A. Yao, “RAPID: Randomized Pharmacophore Identification for drug design,” in ACM Conference on Computational Geometry, Nice, France, 1997, pp. 324–333.
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  7. B. Barraquand, L. E. Kavraki, J.-C. Latombe, T.-Y. Li, R. Motwani, and P. Raghavan, “A Random Sampling Scheme for Robot Path Planning,” International Journal of Robotics Research, vol. 16, no. 6, pp. 759–774, 1997.
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1996

  1. P. W. Finn, D. Halperin, L. E. Kavraki, J.-C. Latombe, R. Motwani, C. Shelton, and S. Venkat, “Geometric Manipulation of Flexible Ligands,” in LNCS Series Applied Computational Geometry - Towards Geometric Engineering, 1996, vol. 1148, pp. 67–78. Book includes selected papers from The ACM Workshop on Applied Computational Geometry, Philadelphia, May 1996
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  2. L. E. Kavraki, P. Švestka, J.-C. Latombe, and M. Overmars, “Probabilistic Roadmaps for Path Planning in High Dimensional Configuration Spaces,” IEEE Transactions on Robotics and Automation, vol. 12, no. 4, pp. 566–580, 1996.
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  3. L. E. Kavraki, M. N. Kolountzakis, and J.-C. Latombe, “Analysis of Probabilistic Roadmaps for Path Planning,” in Proceeedings of The 1996 International Conference on Robotics and Automation (ICRA 1996), Minneapolis, MN, 1996, pp. 3020–3026.
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  4. B. Barraquand, L. E. Kavraki, J.-C. Latombe, T.-Y. Li, R. Motwani, and P. Raghavan, “A Random Sampling Scheme for Robot Path Planning,” in Robotics Research, North Holland, 1996, pp. 249–264. Book contains selected papers form the 7th International Conference on Robotics Research (ISRR), 1996
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1995

  1. L. E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan, “Randomized Query Processing in Robot Path Planning,” in Proceedings of the 27th Annual ACM Symposium on Theory of Computing (STOC), Las Vegas, NV, 1995, pp. 353–362.
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  2. R. H. Wilson, L. E. Kavraki, J.-C. Latombe, and T. Lozano-Perez, “Two-Handed Assembly Sequencing,” International Journal of Robotics Research, vol. 14, no. 4, pp. 335–350, 1995.
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  3. L. E. Kavraki, “On the Number of Equilibrium Placements of Mass Distributions in Elliptic Potential Fields,” Computer Science Department, Stanford University, 1559, 1995.
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  4. L. E. Kavraki, “Computation of Configuration Space Obstacles Using the Fast Fourier Transform,” IEEE Transactions on Robotics and Automation, vol. 11, no. 3, pp. 408–413, 1995.
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  5. L. E. Kavraki and M. N. Kolountzakis, “Partitioning an Assembly into Connected Parts is NP-hard,” Information Processing Letters, vol. 55, pp. 159–165, 1995.
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1994

  1. A. Schweikard, R. Tombropoulos, L. E. Kavraki, J. Adler, and J.-C. Latombe, “Treatment Planning for a Radiosurgical System with General Kinematics,” in Proceedings of the IEEE/RJS International Conference on Robotics and Automation (ICRA), San Diego, CA, 1994, pp. 1764–1771.
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  2. L. E. Kavraki and J.-C. Latombe, “Randomized Preprocessing of Configuration Space for Path Planning: Articulated Robots,” in Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS), Munchen, Germany, 1994, pp. 1764–1771.
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  3. L. E. Kavraki and J.-C. Latombe, “Randomized Preprocessing of Configuration Space for Fast Path Planning,” in Proceedings of the International Conference on Robotics and Automation (ICRA), San Diego, CA, 1994, pp. 2138–2139.
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1993

  1. L. E. Kavraki, “Computation of configuration-space obstacles using the fast Fourier transform,” in IEEE International Conference on Robotics and Automation, 1993, vol. 3, pp. 255–261.
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  2. L. E. Kavraki, J.-C. Latombe, and R. H. Wilson, “On the Complexity of Assembly Partitioning,” Information Processing Letters, vol. 48, no. 5, pp. 229–235, 1993.
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