Redundancy, Efficiency and Robustness in Multi-Robot Coverage

Area coverage is an important task for mobile robots, with many real-world applications. Motivated by potential efficiency and robustness improvements, there is growing interest in the use of multiple robots in coverage. Previous investigations of multi-robot coverage focuses on completeness and eliminating redundancy, but does not formally address robustness, nor examine the impact of the initial positions of robots on the coverage time. Indeed, a common assumption is that non-redundancy leads to improved coverage time. We address robustness and efficiency in a family of multi-robot coverage algorithms, based on spanning-tree coverage of approximate cell decomposition. We analytically show that the algorithms are robust, in that as long as a single robot is able to move, the coverage will be completed. We also show that non-redundant (non-back tracking) versions of the algorithms have a worst-case coverage time virtually identical to that of a single robot—thus no performance gain is guaranteed in non-redundant coverage. Moreover, this worst-case is in fact common in real-world applications. Surprisingly, however, redundant coverage algorithms lead to guaranteed performance which halves the coverage time even in the worst case.