Hybrid dynamical moving task allocation methodology for distributed multi-robot coordination system

Dynamical moving task allocation in complex environment for distributed multi-robot coordination system is mainly investigated. We proposed a hybrid dynamical moving task allocation method in this paper, when either robots or tasks update their conditions, robots independently select tasks from a combinatorial cost table as to minimize an objective function. And we use two sample time thresholds for robots to decide the conditions of robots and tasks, and reallocate tasks. To validate our approach, we integrated the proposed dynamical moving task allocation method with our previously developed path planning method and applied it to the distributed multi-robot coordination system problem. Simulation results demonstrated the efficiency and robustness of our proposed task allocation method even under communication failures and robots malfunctions.