The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Existing approaches to multirobot coordination separate scheduling and task allocation, but finding the optimal schedule with joint tasks and spatial constraints requires robots to simultaneously solve the scheduling, task allocation, and path planning problems. We present a formal description of the multirobot joint task allocation problem with heterogeneous capabilities and spatial constraints and an instantiation of the problem for the search and rescue domain. We introduce a novel declarative framework for modeling the problem as a mixed integer linear programming (MILP) problem and present a centralized anytime algorithm with error bounds. We demonstrate that our algorithm can outperform standard MILP solving techniques, greedy heuristics, and a market based approach which separates scheduling and task allocation.

Keywords

Multirobot coordination, Integer Linear Programming

Notes

Sponsor: NSF

Associated Center(s) / Consortia: Center for Integrated Manfacturing Decision Systems

Associated Lab(s) / Group(s): Advanced Agent - Robotics Technology Lab

Associated Project(s): Urban Search and Rescue

Number of pages: 6

Note: Thanks too to iLog Corporation for their generous support

Text Reference

Mary Koes, Illah Nourbakhsh, and Katia Sycara, "Heterogeneous Multirobot Coordination with Spatial and Temporal Constraints," Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), June, 2005, pp. 1292-1297.

BibTeX Reference

@inproceedings{Koes_2005_5138,
   author = "Mary Koes and Illah Nourbakhsh and Katia Sycara",
   title = "Heterogeneous Multirobot Coordination with Spatial and Temporal Constraints",
   booktitle = "Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI)",
   pages = "1292-1297",
   publisher = "AAAI Press",
   month = "June",
   year = "2005",
   Notes = "Thanks too to iLog Corporation for their generous support"
}

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