1 May 2008 A bio-inspired swarm robot coordination algorithm for multiple target searching
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The coordination of a multi-robot system searching for multi targets is challenging under dynamic environment since the multi-robot system demands group coherence (agents need to have the incentive to work together faithfully) and group competence (agents need to know how to work together well). In our previous proposed bio-inspired coordination method, Local Interaction through Virtual Stigmergy (LIVS), one problem is the considerable randomness of the robot movement during coordination, which may lead to more power consumption and longer searching time. To address these issues, an adaptive LIVS (ALIVS) method is proposed in this paper, which not only considers the travel cost and target weight, but also predicting the target/robot ratio and potential robot redundancy with respect to the detected targets. Furthermore, a dynamic weight adjustment is also applied to improve the searching performance. This new method a truly distributed method where each robot makes its own decision based on its local sensing information and the information from its neighbors. Basically, each robot only communicates with its neighbors through a virtual stigmergy mechanism and makes its local movement decision based on a Particle Swarm Optimization (PSO) algorithm. The proposed ALIVS algorithm has been implemented on the embodied robot simulator, Player/Stage, in a searching target. The simulation results demonstrate the efficiency and robustness in a power-efficient manner with the real-world constraints.
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Yan Meng, Yan Meng, Jing Gan, Jing Gan, Sachi Desai, Sachi Desai, } "A bio-inspired swarm robot coordination algorithm for multiple target searching", Proc. SPIE 6964, Evolutionary and Bio-Inspired Computation: Theory and Applications II, 696406 (1 May 2008); doi: 10.1117/12.782504; https://doi.org/10.1117/12.782504

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