Emergent behaviour evolution in collective autonomous mobile robots
ICS'08 Proceedings of the 12th WSEAS international conference on Systems
Multi-robot dispatching in a geographically constrained environment
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Real-time robot path planning based on a modified pulse-coupled neural network model
IEEE Transactions on Neural Networks
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In this paper, a neural network approach to task assignment, based on a self-organizing map (SOM), is proposed for a multirobot system in dynamic environments subject to uncertainties. It is capable of dynamically controlling a group of mobile robots to achieve multiple tasks at different locations, so that the desired number of robots will arrive at every target location from arbitrary initial locations. In the proposed approach, the robot motion planning is integrated with the task assignment, thus the robots start to move once the overall task is given. The robot navigation can be dynamically adjusted to guarantee that each target location has the desired number of robots, even under uncertainties such as when some robots break down. The proposed approach is capable of dealing with changing environments. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies