A Discrete Adaptive Auction-Based Algorithm for Task Assignments of Multi-Robot Systems

For reasons of production cost and differences in manufacturing dates for mobile robots, individual robots on a robot team have different processing, movement, and detection abilities. To maximize the potential ability of individual robots and minimize overall exploration time in unknown environments, this paper proposes a novel discrete adaptive auction-based algorithm for coordinating multirobot systems (MRSs). A utility calculation scheme that takes into account the dispersion of teammates is presented, followed by an identical performance index formula that converges to a value for measuring differences in exploration efficiency. The performance measure is taken into account in calculating bids for exploration tasks. We compared our results to other exploration strategies by simulation and results show improved exploration time.