Abstract—Birds, bees, and fish often flock together in groups to find the source of food (target) based on local information. Inspired by this natural phenomenon, flocking control algorithms are designed to coordinate the activities of multiple agents in cluttered and noisy environments, respectively. First, to allow agents to track and observe the target better in cluttered environments, two new approaches are proposed to control the center of mass (CoM) of positions and velocities of all mobile agents in the network (Single- CoM), and the center of mass of positions and velocities of each agent and its neighbors (Multi-CoM), respectively. With these approaches, the flock can better track the target. Second, to deal with noisy measurements we proposed two flocking control algorithms, Multi-CoM-Shrink and Multi- CoM-Cohesion. Based on these algorithms, all agents can form a network and maintain connectivity, even with noisy measurements. We also investigate the stability of our algorithms. The numerical experimental tests are performed to demonstrate the effectiveness of the proposed approach.
Index Terms—Flocking control, Dynamic target tracking, Multi-agent systems, Mobile agent networks
Cite: Hung Manh La and Weihua Sheng, "Multi-Agent Motion Control in Cluttered and Noisy Environments," Journal of Communications, vol. 8, no. 1, pp. 32-46, 2013. Doi: 10.12720/jcm.8.1.32-46
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