Feedback Coordination of Limited Capability Mobile Robots

In some multi-robot applications, such as exploration, predefined task allocation and coordination can fail to function adequately. This failure is attributed to the inability to completely model a robot's interactions with the environment before task execution. Hence, the main focus of this paper is on a feedback coordination mechanism that executes periodically after initial task allocation. This feedback mechanism monitors the individual and group performance of worker robots. If the performance of a worker robot is unsatisfactory, a task reallocation algorithm adjusts the task-robot combinations of the team. Three cases of unsatisfactory robot performance that can be detected by the feedback mechanism include: complete failure, partial failure, and poor performance. The task allocation and coordination strategy is applied to a multi-robot exploration task. Initial results from experiments in various types of environments indicate that the feedback coordination mechanism successfully identifies the three forms of robot failure, and improves the system's performance.