Fast, Anytime Motion Planning for Prehensile Manipulation in Clutter
Fast, Anytime Motion Planning for Prehensile Manipulation in Clutter
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快速、随时的运动规划，可在杂乱中进行预操控
DOI：
10.1109/humanoids.2018.8624939
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Kostas E. Bekris
中科院分区：
文献类型：
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作者：
A. Kimmel;Rahul Shome;Zakary Littlefield;Kostas E. Bekris
已经开发了许多方法来规划用于拾取和放置的机器人手臂的运动，范围从局部优化到全局搜索技术，这对于稀疏放置的对象是有效的。然而，在许多现实世界的设置中，密集的杂乱仍然会对成功率、计算时间和解决方案的质量产生不利影响。目前的工作整合现有的方法工具，并提出了一个框架，实现高成功率的混乱与随时性能。该想法是首先通过忽略手臂来有效地探索较低维度的末端执行器的任务空间，并且构建导航函数的离散近似，该导航函数引导末端执行器朝向可用抓握或对象放置的集合。这是在线执行的，没有场景的先验知识。然后，一个知情的采样为基础的规划器，整个手臂使用雅可比基转向，以达到有前途的终端执行器的任务空间的指导。虽然知情，该方法也是全面的，并允许随着时间的推移，如果任务空间的指导没有导致解决方案的替代路径的探索。本文评估了所提出的方法对替代品中挑选或放置不同数量的杂波与不同的末端执行器的各种机器人机械手的任务。结果表明，该方法可靠地提供更高质量的解决方案路径更快，具有更高的成功率相对于替代品。
Many methods have been developed for planning the motion of robotic arms for picking and placing, ranging from local optimization to global search techniques, which are effective for sparsely placed objects. Dense clutter, however, still adversely affects the success rate, computation times, and quality of solutions in many real-world setups. The current work integrates tools from existing methodologies and proposes a framework that achieves high success ratio in clutter with anytime performance. The idea is to first explore the lower dimensional end effector's task space efficiently by ignoring the arm, and build a discrete approximation of a navigation function, which guides the end effector towards the set of available grasps or object placements. This is performed online, without prior knowledge of the scene. Then, an informed sampling-based planner for the entire arm uses Jacobian-based steering to reach promising end effector poses given the task space guidance. While informed, the method is also comprehensive and allows the exploration of alternative paths over time if the task space guidance does not lead to a solution. This paper evaluates the proposed method against alternatives in picking or placing tasks among varying amounts of clutter for a variety of robotic manipulators with different end-effectors. The results suggest that the method reliably provides higher quality solution paths quicker, with a higher success rate relative to alternatives.