Object placement as inverse motion planning
Author(s)Holladay, Anne E.; Barry, Jennifer; Kaelbling, Leslie P.; Lozano-Perez, Tomas
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We present an approach to robust placing that uses movable surfaces in the environment to guide a poorly grasped object into a goal pose. This problem is an instance of the inverse motion planning problem, in which we solve for a configuration of the environment that makes desired trajectories likely. To calculate the probability that an object will take a particular trajectory, we model the physics of placing as a mixture model of simple object motions. Our algorithm searches over the possible configurations of the object and environment and uses this model to choose the configuration most likely to lead to a successful place. We show that this algorithm allows the PR2 robot to execute placements that fail with traditional placing implementations.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2013 IEEE International Conference on Robotics and Automation
Institute of Electrical and Electronics Engineers (IEEE)
Holladay, Anne, Jennifer Barry, Leslie Pack Kaelbling, and Tomas Lozano-Perez. “Object Placement as Inverse Motion Planning.” 2013 IEEE International Conference on Robotics and Automation Automation (ICRA) Karlsruhe, Germany, May 6-10, 2013. pp.3715-3721.
Author's final manuscript