Learn all about Multi-Agent Path Finding (MAPF)
W. Hoenig, S. Kiesel, A. Tinka, J. Durham and N. Ayanian. Persistent and Robust Execution of MAPF Schedules in Warehouses. IEEE Robotics and Automation Letters, 4, (2), 1125-1131, 2019.
Abstract: Multi-Agent Path Finding (MAPF) is a well-studied problem in Artificial Intelligence that can be solved quickly in practice when using simplified agent assumptions. However,real-world applications, such as warehouse automation, require physical robots to function over long time horizons without collisions. We present an execution framework that can use existing single-shot MAPF planners and ensures robust execution in the presence of unknown or time-varying higher-order dynamic limits, unforeseen robot slow-downs, and unpredictable obstacle appearances. Our framework also naturally enables the overlap of re-planning and execution for persistent operation and requires little communication between robots and the centralized planner. We demonstrate our approach in warehouse simulations and in a mixed reality experiment using differential drive robots. We believe that our solution closes the gap between recent research in the artificial intelligence community and real-world applications.