Solving task planning problems involving multiple objects and multiple robotic arms poses scalability challenges. Such problems involve not only coordinating multiple high-DoF arms, but also searching through possible sequences of actions including object placements, and handoffs. The current work identifies a useful connection between multi-arm rearrangement and recent results in multi-body path planning on graphs with vertex capacity constraints. Solving a synchronized multi-arm rearrangement at a high-level involves reasoning over a modal graph, where nodes correspond to stable object placements and object transfer states by the arms. Edges of this graph correspond to pick, placement and handoff operations. The objects can be viewed as pebbles moving over this graph, which has capacity constraints. For instance, each arm can carry a single object but placement locations can accumulate many objects. Efficient integer linear programming-based solvers have been proposed for the corresponding pebble problem. The current work proposes a heuristic to guide the task planning process for synchronized multi-arm rearrangement. Results indicate good scalability to multiple arms and objects, and an algorithm that can find high-quality solutions fast and exhibiting desirable anytime behavior.

中文翻译：

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由具有容量约束的模式图引导的同步多臂重排

解决涉及多个对象和多个机械臂的任务规划问题带来了可扩展性挑战。此类问题不仅涉及协调多个高自由度臂，还涉及搜索可能的动作序列，包括对象放置和切换。当前的工作确定了多臂重排与具有顶点容量约束的图上多体路径规划的最新结果之间的有用联系。在高层解决同步多臂重排涉及对模态图进行推理，其中节点对应于臂的稳定对象放置和对象转移状态。该图的边对应于拾取、放置和切换操作。可以将对象视为在此图上移动的鹅卵石，该图具有容量限制。例如，每个手臂可以携带一个物体，但放置位置可以堆积许多物体。已经针对相应的鹅卵石问题提出了基于整数线性规划的高效求解器。当前的工作提出了一种启发式方法来指导同步多臂重排的任务规划过程。结果表明对多个手臂和物体具有良好的可扩展性，并且该算法可以快速找到高质量的解决方案并表现出理想的任何时间行为。