论文标题
杂物中目标检索的快速和弹性操纵计划
Fast and resilient manipulation planning for target retrieval in clutter
论文作者
论文摘要
本文为机器人操纵器提供了一个任务和运动计划（TAMP）框架，以便从混乱中检索目标对象。我们考虑具有高密度的限制空间中对象的配置，因此不存在无碰撞路径。机器人必须重新安置某些对象以在没有冲突的情况下检索目标。为了快速完成对象重排，该机器人旨在优化通常决定tamp框架效率的拾取操作数量。 我们提出了一个任务计划者，其中包含运动计划，以生成可执行计划，旨在最大程度地减少采摘动作的数量。除了完全已知和静态的环境外，我们的方法还可以处理不确定的和动态的情况。与基线方法相比，我们的方法显示出可减少拾取动作的数量（例如，在具有20个对象的已知静态环境中，至少有28.0％的降低）。
This paper presents a task and motion planning (TAMP) framework for a robotic manipulator in order to retrieve a target object from clutter. We consider a configuration of objects in a confined space with a high density so no collision-free path to the target exists. The robot must relocate some objects to retrieve the target without collisions. For fast completion of object rearrangement, the robot aims to optimize the number of pick-and-place actions which often determines the efficiency of a TAMP framework. We propose a task planner incorporating motion planning to generate executable plans which aims to minimize the number of pick-and-place actions. In addition to fully known and static environments, our method can deal with uncertain and dynamic situations incurred by occluded views. Our method is shown to reduce the number of pick-and-place actions compared to baseline methods (e.g., at least 28.0% of reduction in a known static environment with 20 objects).
