Object placement as inverse motion planning
Name
Kaelbling_Object placement.pdf
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1.84 MB
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Adobe PDF
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Author(s)
Holladay, Anne E.
Barry, Jennifer
Kaelbling, Leslie P.
Lozano-Perez, Tomas
Date Issued
May 2013
Journal
2013 IEEE International Conference on Robotics and Automation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
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.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/ICRA.2013.6631099
