5 papers
A Framework for Combining Optimization-Based and Analytic Inverse Kinematics
Thomas Cohn, Lihan Tang, Alexandre Amice +1
Analytic and optimization methods for solving inverse kinematics (IK) problems have been deeply studied throughout the history of robotics. The two strategies have complementary st…
How Well do Diffusion Policies Learn Kinematic Constraint Manifolds?
Lexi Foland, Thomas Cohn, Adam Wei +3
Diffusion policies have shown impressive results in robot imitation learning, even for tasks that require satisfaction of kinematic equality constraints. However, task performance…
Sampling-Based Motion Planning with Discrete Configuration-Space Symmetries
Thomas Cohn, Russ Tedrake
When planning motions in a configuration space that has underlying symmetries (e.g. when manipulating one or multiple symmetric objects), the ideal planning algorithm should take a…
Faster Algorithms for Growing Collision-Free Convex Polytopes in Robot Configuration Space
Peter Werner, Thomas Cohn, Rebecca H. Jiang +4
We propose two novel algorithms for constructing convex collision-free polytopes in robot configuration space. Finding these polytopes enables the application of stronger motion-pl…
Planning Shorter Paths in Graphs of Convex Sets by Undistorting Parametrized Configuration Spaces
Shruti Garg, Thomas Cohn, Russ Tedrake
Optimization based motion planning provides a useful modeling framework through various costs and constraints. Using Graph of Convex Sets (GCS) for trajectory optimization gives gu…