Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning
Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning
复制标题
多智能体机器人装配规划的最优顺序任务分配和路径查找
DOI：
10.1109/icra40945.2020.9197527
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Mykel J. Kochenderfer
中科院分区：
文献类型：
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作者：
Kyle Brown;Oriana Peltzer;Martin A. Sehr;M. Schwager;Mykel J. Kochenderfer
我们研究了具有任务间优先约束的应用中大型机器人团队的顺序任务分配和无碰撞路由问题（例如，任务 A 和任务 B 必须在任务 C 开始之前完成）。此类问题通常发生在机器人制造应用的装配规划中，其中必须先完成子装配，然后才能将其组合形成最终产品。我们提出了一种分层算法来计算问题的跨度最优解决方案。该算法在一组随机生成的问题实例上进行评估，其中机器人必须在“工厂”网格世界环境中的站点之间运输物体。此外，我们在高保真模拟中证明，我们算法的输出可用于生成非完整差动驱动机器人的无碰撞轨迹。
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.
影响因子：
5.2
作者：
W. Hönig;Scott Kiesel;Andrew Tinka;Joseph W. Durham;Nora Ayanian
通讯作者：
W. Hönig;Scott Kiesel;Andrew Tinka;Joseph W. Durham;Nora Ayanian