Dynamic Task Assignment in Robot Swarms
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 Card- Dealerâs 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-Dealerâs, 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. Download: Bibtex: @INPROCEEDINGS{ McLurkin-RSS-05, AUTHOR = {James McLurkin and Daniel Yamins}, TITLE = {Dynamic Task Assignment in Robot Swarms}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2005}, ADDRESS = {Cambridge, USA}, MONTH = {June}, DOI = {10.15607/RSS.2005.I.018} }