Object Reconfiguration with Simulation-Derived Feasible Actions
Object Reconfiguration with Simulation-Derived Feasible Actions
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DOI：
10.1109/icra48891.2023.10160377
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Yiyuan Lee;Wil B. Thomason;Zachary K. Kingston;L. Kavraki
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文献类型：
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作者：
Yiyuan Lee;Wil B. Thomason;Zachary K. Kingston;L. Kavraki
3D对象重新配置包括常见的机器人操作任务，其中一组对象必须通过一系列物理上可行的状态变化移动到所需的最终配置。对象重构通常具有挑战性，因为它需要对确定动作有效性的环境物理进行有效推理。此信息通常在显式转换系统中手动编码。构造这些显式编码是繁琐且容易出错的，并且通常是规划器使用的瓶颈。在这项工作中，我们探索在运动规划器中嵌入物理模拟器，以隐式地发现和指定来自任何状态的有效动作，从而消除了手动指定动作语义的需要。我们的实验表明，由此产生的基于模拟的规划器可以有效地产生物理上有效的重排轨迹的范围内的3D对象重新配置问题，而不需要超过一个环境描述和开始和目标的安排。
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.