3D object reconfiguration encompasses common robot manipulation tasks in which a set of objects must be moved through a series of physically feasible state changes into a desired final configuration. Object reconfiguration is challenging to solve in general, as it requires efficient reasoning about environment physics that determine action validity. This information is typically manually encoded in an explicit transition system. Constructing these explicit encodings is tedious and error-prone, and is often a bottleneck for planner use. In this work, we explore embedding a physics simulator within a motion planner to implicitly discover and specify the valid actions from any state, removing the need for manual specification of action semantics. Our experiments demonstrate that the resulting simulation-based planner can effectively produce physically valid rearrangement trajectories for a range of 3D object reconfiguration problems without requiring more than an environment description and start and goal arrangements.

翻译：三维物体重配置涉及常见的机器人操作任务，要求一组物体通过一系列物理可行的状态变化，最终达到期望的配置状态。物体重配置的通用求解颇具挑战性，因其需要对决定动作有效性的环境物理特性进行高效推理。此类信息通常需要手动编码至显式转移系统中。构建这类显式编码既繁琐又易出错，往往成为规划器应用的瓶颈。本研究探索将物理仿真器嵌入运动规划器，以隐式发现并定义任意状态下的有效动作，从而消除手动指定动作语义的必要性。实验表明，该基于仿真的规划器无需超出环境描述及初始与目标配置的要求，即可有效生成一系列三维物体重配置问题中物理可行的重排轨迹。