Publications

Books

  1. 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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  2. P. K. Agrawal, L. E. Kavraki, and M. Mason, Robotics: The Algorithmic Perspective. Natick MA: AK Peters, 1998.
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Proceedings

  1. L. E. Kavraki, D. Hsu, and J. Buchli, Eds., Robotics Science and Systems XI. 2015.
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  2. D. Fox, L. E. Kavraki, and H. Kurniawati, Eds., Robotics Science and Systems X. 2014.
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Journal Articles

  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. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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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  26. 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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  27. 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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  28. 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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  29. 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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  30. 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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  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  38. 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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  39. 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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  40. 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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  41. 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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  42. 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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  43. 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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  44. 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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  45. 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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  46. 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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  47. 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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  48. 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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  49. 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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  50. 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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  51. 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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  52. 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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  53. 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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  54. 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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  55. 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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  56. 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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  57. 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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  58. 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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  59. 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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  60. 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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  61. 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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  62. 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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  63. 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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  64. 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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  65. 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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  66. 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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  67. 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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  68. 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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  69. 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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  70. 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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  71. 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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  72. 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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  73. 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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  74. 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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  75. 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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  76. 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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  77. 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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  78. 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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  79. 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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  80. A. Dhanik and L. E. Kavraki, “Protein-ligand interactions: computational docking,” Encyclopedia of Life Sciences, 2012.
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  81. 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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  82. 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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  83. 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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  84. 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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  85. 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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  86. 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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  87. 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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  88. 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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  89. 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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  90. 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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  91. 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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  92. 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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  93. 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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  94. 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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  95. 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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  96. 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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  97. 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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  98. 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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  99. 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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  100. 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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  101. 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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  102. 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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  103. 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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  104. 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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  105. 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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  106. 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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  107. 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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  108. 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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  109. 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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  110. 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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  111. 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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  112. 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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  113. 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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  114. 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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  115. 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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  116. 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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  117. 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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  118. 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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  119. 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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  120. 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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  121. 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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  122. 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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  123. 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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  124. 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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  125. 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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  126. 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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  127. 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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  128. 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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  129. 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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  130. P. W. Finn and L. E. Kavraki, “Computational Approaches to Drug Design,” Algorithmica, vol. 25, pp. 347–371, 1999.
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  131. 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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  132. 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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  133. 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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  134. 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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  135. 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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  136. 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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  137. 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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  138. 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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  139. 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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Book Chapters

  1. 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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  2. 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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  3. 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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  4. 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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  5. D. Schwarz and L. E. Kavraki, “Protein-Ligand Interactions: Computational Docking,” in Encyclopedia of Life Sciences, Wiley, 2007, p. 4105.
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  6. 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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  7. 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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  8. 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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  9. 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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  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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  11. 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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  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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Conference Articles

  1. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. 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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  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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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  26. 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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  27. 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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  28. 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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  29. 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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  30. 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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  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  38. 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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  39. 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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  40. 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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  41. 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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  42. 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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  43. 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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  44. 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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  45. 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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  46. 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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  47. 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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  48. 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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  49. 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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  50. 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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  51. 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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  52. 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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  53. 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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  54. 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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  55. 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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  56. 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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  57. 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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  58. 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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  59. 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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  60. 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.