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It is desirable to self-organize mobile sensor networks to form different yet suitable patterns to adapt to environment changes dynamically in uncertain environments. Inspired by biological morphogenesis which is guided by gene regulatory networks (GRNs), in this study, we propose a GRN-based approach to self-organization of mobile sensor networks in dynamic, uncertain environments. Instead of predefining...
This paper presents a new object tracking algorithm by using the particle swarm optimization (PSO), which is a bio-inspired population-based searching algorithm. Firstly the potential solutions of the problem are projected into a state space called solution space where every point in the space presents a potential solution. Then a group of particles are initialized and start searching in this solution...
Some common issues exist in the bio-inspired algorithms for a multi-robot system include considerable randomness of the robot movement during coordination and unevenly distributed robots in a multi-task environment. To address these issues, a self-adaptive distributed multi-task allocation method in a multi-robot system is proposed in this paper. In this method, each robot only communicates with its...
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