Task planning in robot groups for problems with implicitly defined scenarios based on finite-state automata technique

This paper provides a methodology for planning collective actions of a group of autonomous robots to solve a multi-stage task in a partially determined environment when operation scenario is not known in advance. We describe finite-automata model of the multi-stage problem and propose a planning algorithm for dynamic formation of the scenario and its parallel-sequential execution. The resulting network of finite state machines allows not only to plan actions of the robots, but also to monitor task execution progress in real-time. Experimental results presented in the paper fully confirm the reliability of the proposed approach.