TY - GEN
T1 - Weighted voting game based multi-robot team formation for distributed area coverage
AU - Cheng, Ke
AU - Dasgupta, Prithviraj
PY - 2010
Y1 - 2010
N2 - In the multi-robot area coverage problem, a group of mobile robots have to cover an initially unknown environment using a sensor or coverage tool attached to each robot. Multi-robot area coverage is encountered in many applications of multirobot systems including unmanned search and rescue, aerial reconnaissance, robotic demining, automatic lawn mowing, and inspection of engineering structures. We envisage that multi-robot coverage can be performed efficiently if robots are coordinated to form small teams while covering the environment. In this paper, we use a technique from coalitional game theory called a weighted voting game that allows each robot to dynamically identify other team members and form teams so that the efficiency of the area coverage operation is improved. We propose and evaluate a novel technique of computing the weights of a weighted voting game based on each robot's coverage capability and finding the best minimal winning coalition(BMWC). We theoretically prove the feasibility of our model, and give algorithms to find the BMWC as well. We have also evaluated the performance of our algorithms within a robot simulation platform using up to 40 robots.
AB - In the multi-robot area coverage problem, a group of mobile robots have to cover an initially unknown environment using a sensor or coverage tool attached to each robot. Multi-robot area coverage is encountered in many applications of multirobot systems including unmanned search and rescue, aerial reconnaissance, robotic demining, automatic lawn mowing, and inspection of engineering structures. We envisage that multi-robot coverage can be performed efficiently if robots are coordinated to form small teams while covering the environment. In this paper, we use a technique from coalitional game theory called a weighted voting game that allows each robot to dynamically identify other team members and form teams so that the efficiency of the area coverage operation is improved. We propose and evaluate a novel technique of computing the weights of a weighted voting game based on each robot's coverage capability and finding the best minimal winning coalition(BMWC). We theoretically prove the feasibility of our model, and give algorithms to find the BMWC as well. We have also evaluated the performance of our algorithms within a robot simulation platform using up to 40 robots.
KW - Area coverage
KW - Weighted voting games
KW - Winning coalitions
UR - http://www.scopus.com/inward/record.url?scp=79955655293&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79955655293&partnerID=8YFLogxK
U2 - 10.1145/1967112.1967114
DO - 10.1145/1967112.1967114
M3 - Conference contribution
AN - SCOPUS:79955655293
SN - 9781450302500
T3 - ACM International Conference Proceeding Series
SP - 9
EP - 15
BT - 3rd International Symposium on Practical Cognitive Agents and Robots, PCAR 2010 - Proceedings of an AAMAS 2010 Workshop
T2 - 3rd International Symposium on Practical Cognitive Agents and Robots, PCAR 2010
Y2 - 10 May 2010 through 10 May 2010
ER -