Auction-based multi-robot task allocation in COMSTAR Export

@inproceedings{Hoeing2007Auctionbased, abstract = {Over the past few years, swarm based systems have emerged as an attractive paradigm for building large scale distributed systems composed of numerous independent but coordinating units. In our previous work, we have developed a protoype system called COMSTAR (Cooperative Multi-agent Systems for automatic TArget Recognition) using a swarm of unmanned aerial vehicles(UAVs) that is capable of identifying targets in software simulations of reconnaissance operations. Experimental results from the simulations of the COMSTAR system show that task selection among the UAVs is a crucial operation that determines the overall efficiency of the system. Previously described techniques for task selection among swarm units use a centralized server such as a ground control station to coordinate the activities of the swarm units. However, such systems are not truly distributed since the behavior of the swarm units is predominantly directed by the centralized server's task allocation algorithm. In this paper we focus on the problem of distributed task selection in a swarmed system where each swarm unit decides on the tasks it will execute by sharing information and coordinating its actions with other swarm units without the intervention of a centralized ground control station supervising its activities. Specifically, we build our task selection algorithm on an auction-based algorithm for task selection in robotic swarms described by Kalra et al. We report experimental results in a simulated environment with 18 robots and 20 tasks and compare the performance of our auction-based algorithm with other heuristic-based task selection strategies in multi-agent swarms. Our simulation results show that the auction-based algorithm improves the task completion times by 30-60\% and reduces the communication overhead by as much as 90\% with respect to other heuristic-based strategies maintaining similar performance in load balancing.}, address = {New York, NY, USA}, author = {Hoeing, Matthew and Dasgupta, Prithviraj and Petrov, Plamen and O'Hara, Stephen}, booktitle = {AAMAS '07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems}, citeulike-article-id = {3400660}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1329462}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1329125.1329462}, citeulike-linkout-2 = {http://dx.doi.org/http://dx.doi.org/10.1145/1329125.1329462}, citeulike-linkout-3 = {http://dx.doi.org/10.1145/1329125.1329462}, comment = {COMSTAR - an automated target recognition system. Simulates 20-50 UAVs, need multiple independent observations before object is marked as target (needs collaboration between agents to be sure). ` Uses auction to find nearest robots and request a visit from them to verify the target. + Swarm robotics references - Very simple task model: Get n+ robots to visit same place at roughly the same time. - I feel the comparison of results is maybe skewed in their favour? - Metrics such as mean time to identify target, targets successfully identified not addressed.}, doi = {10.1145/1329125.1329462}, isbn = {978-81-904262-7-5}, keywords = {auction, automated-target-recognition, comstar, distributed-auction, distributed-robotics, stigmergy, uav}, location = {Honolulu, Hawaii}, pages = {1--8}, posted-at = {2008-10-13 15:01:26}, priority = {0}, publisher = {ACM}, title = {Auction-based multi-robot task allocation in COMSTAR}, url = {http://dx.doi.org/10.1145/1329125.1329462}, year = {2007} }

TY - CONF ID - Hoeing2007Auctionbased L3 - citeulike-article-id:3400660 N2 - Over the past few years, swarm based systems have emerged as an attractive paradigm for building large scale distributed systems composed of numerous independent but coordinating units. In our previous work, we have developed a protoype system called COMSTAR (Cooperative Multi-agent Systems for automatic TArget Recognition) using a swarm of unmanned aerial vehicles(UAVs) that is capable of identifying targets in software simulations of reconnaissance operations. Experimental results from the simulations of the COMSTAR system show that task selection among the UAVs is a crucial operation that determines the overall efficiency of the system. Previously described techniques for task selection among swarm units use a centralized server such as a ground control station to coordinate the activities of the swarm units. However, such systems are not truly distributed since the behavior of the swarm units is predominantly directed by the centralized server's task allocation algorithm. In this paper we focus on the problem of distributed task selection in a swarmed system where each swarm unit decides on the tasks it will execute by sharing information and coordinating its actions with other swarm units without the intervention of a centralized ground control station supervising its activities. Specifically, we build our task selection algorithm on an auction-based algorithm for task selection in robotic swarms described by Kalra et al. We report experimental results in a simulated environment with 18 robots and 20 tasks and compare the performance of our auction-based algorithm with other heuristic-based task selection strategies in multi-agent swarms. Our simulation results show that the auction-based algorithm improves the task completion times by 30-60% and reduces the communication overhead by as much as 90% with respect to other heuristic-based strategies maintaining similar performance in load balancing. CY - Honolulu, Hawaii SN - 978-81-904262-7-5 AD - New York, NY, USA EP - 8 TI - Auction-based multi-robot task allocation in COMSTAR PB - ACM T2 - AAMAS '07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems SP - 1 KW - auction KW - automated-target-recognition KW - comstar KW - distributed-auction KW - distributed-robotics KW - stigmergy KW - uav N1 - COMSTAR - an automated target recognition system. Simulates 20-50 UAVs, need multiple independent observations before object is marked as target (needs collaboration between agents to be sure). ` Uses auction to find nearest robots and request a visit from them to verify the target. + Swarm robotics references - Very simple task model: Get n+ robots to visit same place at roughly the same time. - I feel the comparison of results is maybe skewed in their favour? - Metrics such as mean time to identify target, targets successfully identified not addressed. AU - Hoeing, Matthew AU - Dasgupta, Prithviraj AU - Petrov, Plamen AU - O'Hara, Stephen PY - 2007/// UR - http://dx.doi.org/10.1145/1329125.1329462 ER -