Planar in-hand manipulation via motion cones
Name
0278364919880257.pdf
Description
Published version
Size
3.94 MB
Format
Adobe PDF
Checksum (MD5)
b83457290e963d12df51e78ee13802e8
Author(s) • •
Chavan Dafle, Nikhil Narsingh
Holladay, Rachel
Rodriguez, Alberto
Date Issued
March 2020
Journal
International Journal of Robotics Research
Publisher
SAGE Publications
Citation
Chavan-Dafle, Nikhil et al. "Planar in-hand manipulation via motion cones." International Journal of Robotics Research 39, 2-3 (March 2020): 163-182.
Version
Final published version
Abstract
In this article, we present the mechanics and algorithms to compute the set of feasible motions of an object pushed in a plane. This set is known as the motion cone and was previously described for non-prehensile manipulation tasks in the horizontal plane. We generalize its construction to a broader set of planar tasks, such as those where external forces including gravity influence the dynamics of pushing, or prehensile tasks, where there are complex frictional interactions between the gripper, object, and pusher. We show that the motion cone is defined by a set of low-curvature surfaces and approximate it by a polyhedral cone. We verify its validity with thousands of pushing experiments recorded with a motion tracking system. Motion cones abstract the algebra involved in the dynamics of frictional pushing and can be used for simulation, planning, and control. In this article, we demonstrate their use for the dynamic propagation step in a sampling-based planning algorithm. By constraining the planner to explore only through the interior of motion cones, we obtain manipulation strategies that are robust against bounded uncertainties in the frictional parameters of the system. Our planner generates in-hand manipulation trajectories that involve sequences of continuous pushes, from different sides of the object when necessary, with 5–1,000 times speed improvements to equivalent algorithms.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1177/0278364919880257