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Spring 2010 GRASP Seminar – Leslie Kaelbling, Massachusetts Institute of Technology CSAIL, “Robust Grasping Under Uncertainty”

April 30, 2010 @ 11:00 am - 12:00 pm

Abstract: Most work on robot grasping concentrates on geometric questions of how
best to place the fingers in order to achieve a stable grasp, and
typically assumes that the relative pose of the robot and object are
known fairly accurately. In this talk, I will outline an approach to
robust grasping when the object’s pose is initially estimated using
vision or some other sensor modality with a fair amount of residual
uncertainty. We perform a sequential decision process to gather
information from tactile sensors on the robot hand, to refine the
position estimate and ultimately grasp the object with high reliability.Joint work with Kaijen Hsiao and Tomas Lozano-Perez


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Leslie Pack Kaelbling is Professor of Computer Science and Engineering at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. She has made research contributions to decision-making under uncertainty, learning, and sensing with applications to robotics, with a particular focus on reinforcement learning and planning in partially observable domains.

She holds an A.B in Philosphy and a Ph.D. in Computer Science from Stanford University, and has had research positions at SRI International and Teleos Research and a faculty position at Brown University. She is the recipient of the US National Science Foundation Presidential Faculty Fellowship, the IJCAI Computers and Thought Award, and several teaching prizes. She was the founder and editor-in-chief of the Journal of Machine Learning Research, and is a fellow of the AAAI.


April 30, 2010
11:00 am - 12:00 pm
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