论文标题
大规模对象分类的关节推格动作空间中的决策空间
Decision Making in Joint Push-Grasp Action Space for Large-Scale Object Sorting
论文作者
论文摘要
我们为大规模（联合国）标记的对象排序任务提供了一个计划者，该任务使用两种类型的操纵操作：高架抓握和平面推动。掌握动作在温和的假设下提供了完整的保证，而平面推动是一种加速策略，可以立即移动多个对象。我们的主要贡献是双重的：（1）我们提出了一种二线计划算法。我们的高级规划师根据成本模型在推动和抓住动作之间做出了有效的，近乎最佳的选择。我们的低级计划者计算一步贪婪的推动或抓住动作。 （2）我们提出了一个新型的低级推动计划者，可以在半差异的搜索空间中找到一步贪婪的推动动作。搜索空间的结构使我们能够有效地表明，对于排序最多$ 200 $的对象，我们的计划者可以在台式机上找到$ 10 $秒的计算的近乎最佳动作。
We present a planner for large-scale (un)labeled object sorting tasks, which uses two types of manipulation actions: overhead grasping and planar pushing. The grasping action offers completeness guarantee under mild assumptions, and planar pushing is an acceleration strategy that moves multiple objects at once. Our main contribution is twofold: (1) We propose a bilevel planning algorithm. Our high-level planner makes efficient, near-optimal choices between pushing and grasping actions based on a cost model. Our low-level planner computes one-step greedy pushing or grasping actions. (2) We propose a novel low-level push planner that can find one-step greedy pushing actions in a semi-discrete search space. The structure of the search space allows us to efficient We show that, for sorting up to $200$ objects, our planner can find near-optimal actions with $10$ seconds of computation on a desktop machine.
