Abstract-A large group of robots will often be partitioned into subgroups, each subgroup performing a different task. This paper presents four distributed algorithms for assigning swarms of homogenous robots to subgroups to meet a specified global task distribution. Algorithm Random-Choice selects tasks randomly, but runs in constant time. Algorithm Extreme-Comm compiles a complete inventory of all the robots on every robot, runs quickly, but uses a great deal of communication. The CardDealer's algorithm assigns tasks to individual robots sequentially, using minimal communications but a great deal of time. The TreeRecolor algorithm is a compromise between Extreme-Comm and Card-Dealer's, balancing communications use and running time. The three deterministic algorithms drive the system towards the desired assignment of subtasks with high accuracy. We implement the algorithms on a group of 25 iRobot SwarmBots, and collect and analyze performance data.
James McLurkin REF proposed three different methods of task assignment in robot swarms: random-choice algorithm, which is extremely communication extensive and inefficient, card-dealer's algorithm, which assigns tasks to individual robots sequentially, using minimal communications but a great deal of time, and tree-recolor algorithm, which is a compromise between extreme-communication and carddealer's, balancing communications use and running time.
Dynamic Task Assignment in Robot Swarms
Proceedings of Robotics: Science and Systems
Computer Science