Sampling Based Motion Planning with Reachable Volumes
PhD student, Parasol Lab, Department of Computer Science and Engineering
Texas A&M University
Tuesday, June 28, 2016|
12:00pm - 1:00pm
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About the Event
Motion planning for constrained systems is a version of the motion planning problem in which the motion of a robot is limited by constraints. For example, one can require that a humanoid robot such as a PR2 remain upright by constraining its torso to be above its base or require that an object such as a bucket of water remain upright by constraining the vertices of the object to be parallel to the robot’s base. Such problems are particularly difficult because the constraints form a manifold in C-space, and planning must be restricted to this manifold.
Troy McMahon is a PhD student in the Parasol Lab in the Department of Computer Science and Engineering at Texas A&M University advised by Professor Nancy M. Amato. He received a B.S. from the University of Massachusetts in 2005 where he graduated with a double major in Computer Science and Physics. His research interests include motion planning, robotics, computational biology, computational geometry, artificial intelligence, machine learning, parallel algorithms and graphics.
Contact: Stephen Reger
Sponsor(s): CSE Robotics
Open to: Public