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Pre- and Post-Contact Policy Decomposition for Planar Contact Manipulation Under Uncertainty
2014
Robotics: Science and Systems X
We consider the problem of using real-time feedback from contact sensors to create closed-loop pushing actions. To do so, we formulate the problem as a partially observable Markov decision process (POMDP) with a transition model based on a physics simulator and a reward function that drives the robot towards a successful grasp. We demonstrate that it is intractable to solve the full POMDP with traditional techniques and introduce a novel decomposition of the policy into pre-and post-contact
doi:10.15607/rss.2014.x.034
dblp:conf/rss/KovalPS14
fatcat:xsgv2um4zbfitdftgr4rmainbu