Automated negotiation and decision making in multiagent environments
Mutli-agents systems and applications
Multi-Robot Task Allocation in Uncertain Environments
Autonomous Robots
Collision avoidance between UAV clusters using swarm intelligence techniques
International Journal of Systems Science
Networked architecture for multi-robot task reallocation in dynamic environment
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Multiple UAV Coalitions for a Search and Prosecute Mission
Journal of Intelligent and Robotic Systems
Adaptive negotiation in managing wireless sensor networks
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
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A multiple UAV search and attack mission involves searching for targets in an unknown region, followed by attack on the detected targets. An effective mission involves assigning the tasks to UAVs efficiently. Task allocation becomes difficult when the UAVs have limited range to detect the targets and neighbouring UAVs. The UAVs are also subject to limited communication range. With these constraints, allocating tasks efficiently to UAVs become difficult. In this paper, we propose a negotiation scheme that efficiently allocates tasks for multiple UAVs. The performance of the negotiation based task allocation is studied on a battle field scenario. We study the effect of sensor ranges on the task allocation and compare the results with that of greedy strategy and a variation of the negotiation mechanism. The results show that the negotiation based task allocation mechanism performs far better than the greedy strategy. Negotiation with target information exchange between neighbours performs better than without target information exchange, when the sensor radius is low.