Computational Robotics, AI & Biomedicine Lab
Lydia Kavraki giving a keynote at the 2018 IEEE International Conference on Robotics and Automation in Brisbane, Australia
Planning motions for the legged version of Robonaut2 inside the International Space Station.
We have developed a method to explore flexibility of large macromolecules.
In integrated task and motion planning, a search for a sequence of discrete actions is interleaved with finding continuous motions.
We are interested in predicting the binding modes of peptides to both class I (left) and class II (right) MHC receptors.
Asymptotically optimal manifold-constrained motion planning available in OMPL.
Robonaut 2 walking inside the International Space Station powered bymanifold-constrained motion planning.
Motion planning techniques that enhance human-robot interaction (HRI) capabilities.
Navigation through unexplored underwater environments using autonomous underwater vehicles (AUVs). Work in collaboration with University of Girona.
Our group has developed a plugin for the 3D modeling program Blender that allows you to easily plan physically realistic motions.
We have developed a new docking protocol for large ligands and were able to predict new binding modes.
Robust human-robot collaboration is made possible through scalable reactive synthesis.
We are developing algorithms for discovering biological pathways for the production of valuable compounds as well as interactive visualization tools to efficiently present the results.