Emergent Mind

Abstract

This paper presents Contact Mode Guided Manipulation Planning (CMGMP) for 3D quasistatic and quasidynamic rigid body motion planning in dexterous manipulation. The CMGMP algorithm generates hybrid motion plans including both continuous state transitions and discrete contact mode switches, without the need for pre-specified contact sequences or pre-designed motion primitives. The key idea is to use automatically enumerated contact modes of environment-object contacts to guide the tree expansions during the search. Contact modes automatically synthesize manipulation primitives, while the sampling-based planning framework sequences those primitives into a coherent plan. We test our algorithm on fourteen 3D manipulation tasks, and validate our models by executing some plans open-loop on a real robot-manipulator system

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.