Consensus-based task sequencing in decentralized multiple-robot systems using local communication

Behavior-based controllers for complex missions often are more easily designed by decomposing the mission into a series of smaller subtasks. When applying this technique to a multiple-robot system, the entire system should focus its work on one subtask at a time to prevent interference from robots working on conflicting subtasks simultaneously. We present a behavior-based approach to the task-sequencing problem for decentralized multiple-robot systems requiring only local inter-robot communication. Consensus is used to prevent premature task sequencing. Our algorithm is compared to globally-communicative and communication-free strategies. The proposed task-sequencing behavior is found to be efficient with respect to time and energy requirements, and could be applied to many existing decentralized multiple-robot systems.