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Planning for Manipulation with Adaptive Motion Primitives

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4 Author(s)
Benjamin J. Cohen ; Computer and Information Science, GRASP Laboratory, University of Pennsylvania, Philadelphia 19104, USA ; Gokul Subramania ; Sachin Chitta ; Maxim Likhachev

In this paper, we present a search-based motion planning algorithm for manipulation that handles the high dimensionality of the problem and minimizes the limitations associated with employing a strict set of pre-defined actions. Our approach employs a set of adaptive motion primitives comprised of static motions with variable dimensionality and on-the-fly motions generated by two analytical solvers. This method results in a slimmer, multi-dimensional lattice and offers the ability to satisfy goal constraints with precision. To validate our approach, we used a 7DOF manipulator to perform experiments on a real mobile manipulation platform (Willow Garage's PR2). Our results demonstrate the effectiveness of the planner in efficiently navigating cluttered spaces; the method generates consistent, low-cost motion trajectories, and guarantees the search is complete with bounds on the suboptimality of the solution.

Published in:

Robotics and Automation (ICRA), 2011 IEEE International Conference on

Date of Conference:

9-13 May 2011