To safely and efficiently extract an object from the clutter, this paper presents a bimanual manipulation planner in which one hand of the robot is used to slide the target object out of the clutter while the other hand is used to support the surrounding objects to prevent the clutter from collapsing. Our method uses a neural network to predict the physical phenomena of the clutter when the target object is moved. We generate the most efficient action based on the Monte Carlo tree search.The grasping and sliding actions are planned to minimize the number of motion sequences to pick the target object. In addition, the object to be supported is determined to minimize the position change of surrounding objects. Experiments with a real bimanual robot confirmed that the robot could retrieve the target object, reducing the total number of motion sequences and improving safety.

翻译：为了安全高效地从杂乱堆叠中提取目标物体，本文提出一种双臂操作规划方法：机器人一只手用于将目标物体从杂乱堆叠中滑出，另一只手用于支撑周围物体以防止堆叠倒塌。该方法利用神经网络预测目标物体移动时杂乱堆叠的物理现象，并基于蒙特卡洛树搜索生成最高效的动作。规划抓取与滑动动作以最小化拾取目标物体的动作序列数，同时通过确定需被支撑的物体来最小化周围物体的位置变化。在真实双臂机器人上的实验证实，该方法可成功取出目标物体，减少动作序列总数并提升安全性。