Planning pre-grasp manipulation for transport tasks

By Lillian Y. Chang, Siddhartha S. Srinivasa, and Nancy S. Pollard

Published in the Proceedings of th IEEE International Conference on Robotics and Automation (ICRA 2010), May 2010. Finalist for Best Manipulation Paper Award.
Abstract: Studies of human manipulation strategies suggest that pre-grasp object manipulation, such as rotation or sliding of the object to be grasped, can improve task performance by increasing both the task success rate and the quality of load-supporting postures.

In previous demonstrations, pre-grasp object rotation by a robot manipulator was limited to manually-programmed actions. We present a method for automating the planning of pre-grasp rotation for object transport tasks. Our technique optimizes the grasp acquisition point by selecting a target object pose that can be grasped by high-payload manipulator configurations. Careful selection of the transition states leads to successful transport plans for tasks that are otherwise infeasible. In addition, optimization of the grasp acquisition posture also indirectly improves the transport plan quality, as measured by the safety margin of the manipulator payload limits. (Project webpage with videos: [] ; Preprint version of the IEEE ICRA 2010 paper: [http:/])

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