A Combinatorial Auction for Collaborative Planning
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
A genetic algorithm for unmanned aerial vehicle routing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms
Computers and Operations Research
Distributed management of flexible times schedules
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Heterogeneous multirobot coordination with spatial and temporal constraints
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Multi-robot coalition formation
IEEE Transactions on Robotics
Quantitative and qualitative coordination for multi-robot systems
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Considering inter-task resource constraints in task allocation
Autonomous Agents and Multi-Agent Systems
Multi-objective optimization for dynamic task allocation in a multi-robot system
Engineering Applications of Artificial Intelligence
Towards solving an obstacle problem by the cooperation of UAVs and UGVs
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A comparative study between optimization and market-based approaches to multi-robot task allocation
Advances in Artificial Intelligence
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Many applications require teams of robots to cooperatively execute tasks. Among these domains are those in which successful coordination must respect intra-path constraints, which are constraints that occur on the paths of agents and affect route planning. This work focuses on multi-agent coordination for disaster response with intra-path precedence constraints, a compelling application that is not well addressed by current coordination methods. In this domain a group of fire truck agents attempt to address fires spread throughout a city in the wake of a large-scale disaster. The disaster has also caused many city roads to be blocked by impassable debris, which can be cleared by bulldozer robots. A high-quality coordination solution must determine not only a task allocation but also what routes the fire trucks should take given the intra-path precedence constraints and which bulldozers should be assigned to clear debris along those routes.This work presents two methods for generating time-extended coordination solutions--solutions where more than one task is assigned to each agent--for domains with intra-path constraints. Our first approach uses tiered auctions and two heuristic techniques, clustering and opportunistic path planning, to perform a bounded search of possible time-extended schedules and allocations. Our second method uses a centralized, non-heuristic, genetic algorithm-based approach that provides higher quality solutions but at substantially greater computational cost. We compare our time-extended approaches with a range of single task allocation approaches in a simulated disaster response domain.