OMPL is a lightweight, thread-safe, easy to use, and extensible library for sampling-based motion planning. The code is written in C++, includes Python bindings and is released under the BSD license. OMPL is also integrated with ROS. On top of the OMPL library, we have developed OMPL.app: a GUI for rigid body motion planning that allows users to load a variety of mesh formats that define a robot and its environment, define start and goal states, and play around with different planners.
VAMP (Vector Accelerated Motion Planning) is a state-of-the-art motion planning library that leverages single-instruction, multiple-data (SIMD) parallelism to achieve order-of-magnitude speedups in motion planning.
Combined with the collision-affording point tree (CAPT), VAMP is able to achieve microsecond-scale planning times on dynamic, unmodeled environments, enabling real-time motion planning performance.
Planner Arena is a site for benchmarking sampling-based planners. The site is set up to show the performance of implementations of various sampling-based planning algorithms in the Open Motion Planning Library (OMPL).
Robowflex is a library that makes using MoveIt for motion planning easy, providing a high-level C++ API that simplifies many common use-cases in motion planning research, such as benchmarking, customization, and accessing underlying datastructures.
MotionBenchMaker is an extensible, easy-to-use tool to generate and benchmark datasets for manipulation problems. In addition to the tool to generate datasets, MotionBenchMaker comes with a suite of over 40 prefabricated datasets, with 5 different commonly used robots in 8 environments.
The Task-Motion Kit (TMKit) is a framework for Task and Motion Planning. Everyday activities, e.g., setting a table or making coffee, combine discrete decisions about objects and actions with geometric decisions about collision free motion. TMKit jointly reasons about task-level objectives, i.e., choosing actions and objects, and motion-level objectives, i.e., finding collision free paths.
A Pipeline for Selection and Structural HLA Modeling of Conserved Peptides from SARS-related Coronaviruses for Novel Vaccine Development.
Metabolite Translator predicts human metabolites for small molecules including drugs. It is build upon a Neural Machine Translation algorithm representing molecules as sequences using the SMILES notation. Metabolite Translator converts the SMILES of the initial molecule into the SMILES representations of the metabolites that can be possibly formed in the human body. The method has been trained on data that cover metabolism of xenobiotics as well as endogenous compounds and therefore it can predict metabolites through a wide range of enzymes including the enzymes of phase I and phase II drug metabolism.
Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests.
A web server for matching 3D structural motifs in proteins against the proteins in the Protein Data Bank. With a plugin for Chimera the match results can be visualized.