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Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning

机译:多代理机器人装配计划的最佳顺序任务分配和路径查找

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We study the problem of sequential task assignment and collision-free routing for large teams of robots in applications with inter-task precedence constraints (e.g., task A and task B must both be completed before task C may begin). Such problems commonly occur in assembly planning for robotic manufacturing applications, in which sub-assemblies must be completed before they can be combined to form the final product. We propose a hierarchical algorithm for computing makespan-optimal solutions to the problem. The algorithm is evaluated on a set of randomly generated problem instances where robots must transport objects between stations in a "factory" grid world environment. In addition, we demonstrate in high-fidelity simulation that the output of our algorithm can be used to generate collision-free trajectories for non-holonomic differential-drive robots.
机译:我们针对具有任务间优先约束的应用中的大型机器人团队研究顺序任务分配和无冲突路由的问题(例如,任务A和任务B必须同时完成才能开始任务C)。此类问题通常发生在机器人制造应用程序的组装计划中,其中子组件必须先完成才能组合起来才能形成最终产品。我们提出了一种分层算法来计算该问题的最优解决方案。该算法在一组随机生成的问题实例上进行评估,在这些实例中,机器人必须在“工厂”网格世界环境中的站点之间传输对象。此外,我们在高保真仿真中证明了我们算法的输出可用于为非完整的差动驱动机器人生成无碰撞的轨迹。

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