Dynamic Task Assignment in Robot Swarms
James McLurkin, Daniel L. K. Yamins · 2005
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 Card-Dealer's algorithm assigns tasks to individual robots sequentially, using minimal communications but a great deal of time.The Tree-Recolor 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.