Achieving high success rate in dual-arm handover using large number of candidate grasps, handover heuristics, and hierarchical search

Graphical Abstract Many dual-arm handover systems suffer from low success rates since the grasps are limited to a small number of candidate grasps and handover poses. Large number increases success rate but significantly explodes combinatorics and lowers system performance. How to efficiently exploit the large number of grasps and handover poses is a difficulty faced by many dual-arm manipulation researchers. This paper uses handover heuristics and hierarchical search to. challenge the difficulty. For one thing, it samples large number of grasps and handover poses to ensure success handover. For the other, it employs the handover heuristics to reduce combinatorics and the hierarchical search to reduce search space. Leveraging these technique leads to an algorithm that has high computational efficiency and high success rate. We report the algorithm in this paper and examine its performance using both statistical simulation analysis and real-world experiments. Results show that the algorithm can deal with thousands of grasps within a few seconds using a standard PC.

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