A dynamical systems approach to weighted graph matching
Automatica (Journal of IFAC)
Hybrid control structure for multi-robot formation
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
On the communication range in auction-based multi-agent target assignment
IWSOS'11 Proceedings of the 5th international conference on Self-organizing systems
AF-ABLE in the multi agent contest 2009
Annals of Mathematics and Artificial Intelligence
Deploying mobile nodes for maximal energy matching in WSNs
Wireless Communications & Mobile Computing
Decentralized task allocation for surveillance systems with critical tasks
Robotics and Autonomous Systems
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Distributed motion planning of multiple agents raises fundamental and novel problems in control theory and robotics. In particular, in applications such as coverage by mobile sensor networks or multiple target tracking, a great new challenge is the development of motion planning algorithms that dynamically assign targets or destinations to multiple homogeneous agents, not relying on any a priori assignment of agents to destinations. In this paper, we address this challenge using two novel ideas. First, distributed multidestination potential fields are developed that are able to drive every agent to any available destination. Second, nearest neighbor coordination protocols are developed ensuring that distinct agents are assigned to distinct destinations. Integration of the overall system results in a distributed, multiagent, hybrid system for which we show that the mutual exclusion property of the final assignment is guaranteed for almost all initial conditions. Furthermore, we show that our dynamic assignment algorithm will converge after exploring at most a polynomial number of assignments, dramatically reducing the combinatorial nature of purely discrete assignment problems. Our scalable approach is illustrated with nontrivial computer simulations.