Affiliation:
1. Massachusetts Institute of Technology, Cambridge, MA, USA
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.
Funder
MIT-HongKong Alliance
MIT Merrill Lynch Fellowship
mathworks
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software
Cited by
38 articles.
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