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We present an overview of a hierarchical framework for coordinating task-level and motion-level operations in multi-robot systems. Our framework is based on the idea of using simple temporal networks (STNs) to simultaneously reason about: (a) precedence/causal constraints required for task-level coordination; and (b) simple temporal constraints required to ensure the kinematic feasibility of plans. In the plan generation phase, our framework provides a computationally scalable method for generating kinematically feasible plans that achieve high-level tasks for groups of robots. In the execution monitoring phase, our framework provides a method for absorbing the unintended outcomes of plan execution without having to do time-consuming re-planning. We present the key ideas in our framework using the multi-robot path planning problem as a case study.
Supplemental Material for "Overview: A Hierarchical Framework for Plan Generation and Execution Monitoring in Multi-Robot Systems", Hang Ma, Wolfgang Hönig, Nora Ayanian, Liron Cohen, Sven Koenig, T. K. Satish Kumar, Tansel Uras, and Hong Xu. Accepted at IEEE Intelligent Systems 2017.