Parallel asynchronous control strategy for target search with swarm robots

Upon mapping swarm robots search to particle swarm optimisation (PSO) and proposing concept of time-varying character swarm (TVCS), the authors extend PSO to model swarm robotic system. Based on control principle of expected evolution position, an asynchronous communication policy is presented. Robot detects target signals in parallel to decide expected evolution position. The required time steps for completing the distance between two consecutive expected positions depend on kinematics constraints of robot. Meanwhile, robot evaluates positions it passes in every time step, updating its cognition as soon as when a better finding of itself has been found, updating shared information and broadcasting within TVCS if a better finding of swarm appears. Either listening change of shared information or reaching the current expected position, robot starts to compute new expected position and turn out next control round. Simulation results indicate that the presented communication strategy has advantage over popular ones in search efficiency.

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