Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement
Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement
复制标题
DOI：
10.1109/iros47612.2022.9981715
复制
发表时间：
2022-07
期刊：
影响因子：
--
通讯作者：
Kai Gao;Jingjin Yu
中科院分区：
文献类型：
--
作者：
Kai Gao;Jingjin Yu
研究了解决非单调桌面多目标重排任务的机械臂协调问题。在非单调重排任务中，存在复杂的对象-对象依赖关系，需要多次移动某些对象来解决一个实例。在一个大的工作空间里用两只手臂工作时，一些物体必须在机器人之间传递，这进一步复杂化了规划过程。针对具有挑战性的双臂桌面重排问题，我们开发了有效的任务规划算法来调度可在双臂之间适当分布的pick-n-place序列。我们表明，即使不使用复杂的运动规划器，与贪婪方法和单机器人计划的朴素并行化相比，我们的方法也可以节省大量的时间。
We investigate the problem of coordinating two robot arms to solve non-monotone tabletop multi-object re- arrangement tasks. In a non-monotone rearrangement task, complex object-object dependencies exist that require moving some objects multiple times to solve an instance. In working with two arms in a large workspace, some objects must be handed off between the robots, which further complicates the planning process. For the challenging dual-arm tabletop rearrangement problem, we develop effective task planning algorithms for scheduling the pick-n-place sequence that can be properly distributed between the two arms. We show that, even without using a sophisticated motion planner, our method achieves significant time savings in comparison to greedy approaches and naive parallelization of single-robot plans.