This paper presents Contact Mode Guided Manipulation Planning (CMGMP) for 3D quasistatic and quasidynamic rigid body motion planning in dexterous manipulation. The CMGMP algorithm generates hybrid motion plans including both continuous state transitions and discrete contact mode switches, without the need for pre-specified contact sequences or pre-designed motion primitives. The key idea is to use automatically enumerated contact modes of environment-object contacts to guide the tree expansions during the search. Contact modes automatically synthesize manipulation primitives, while the sampling-based planning framework sequences those primitives into a coherent plan. We test our algorithm on fourteen 3D manipulation tasks, and validate our models by executing some plans open-loop on a real robot-manipulator system
翻译:本文介绍三维准静态和准动力硬体运动规划(CMGMP)的3D准静态和准动力操纵的3D硬体运动规划(CMGMP ) 。 CMGMP 算法生成混合运动计划, 包括连续状态转换和离散接触模式开关, 不需要事先指定的接触序列或预先设计的运动原始。 关键的想法是使用自动列举的环境- 对象接触接触的接触模式来引导搜索中的树扩张。 联系模式自动合成操纵原始, 而基于取样的规划框架则将这些原始人排序为连贯的计划。 我们测试14 3D 操作任务的算法, 并通过在真正的机器人- 操纵系统上执行一些计划来验证我们的模型。