Bacterial chemotaxis-inspired strategy for multirobot pattern formation
We present a multirobot hierarchical control strategy inspired by bacterial chemotaxis for multirobot pat-tern generation.This strategy divides the pattern generation process into two stages:the aggregation stage and the pattern generation stage.In the aggregation stage,the fitness function based on the average distance is developed,and its value is employed as the perception input of the robot.Robots aggregate by moving forward or rolling over,similar to bacterial chemotaxis,based on the fitness value change between the current time and the last time to ag-gregate.The search factor is introduced to promote multiple subgroup fusion and enhance the success rate of multi-robot aggregation.In the pattern generation stage,aiming at the problem of rolling-over angle generation of the ro-bot,the decision factor is introduced to assess the degree of the neighbor effect to enhance the success rate of multi-robot pattern generation.The simulation results show that for the hexagon and triangle pattern generation of the mul-tirobot,the average iteration times of the proposed strategy are 25.36 and 93.83,respectively,and the success rates are 83.33%and 96.67%,respectively.The new algorithm is superior to the compared algorithms.
万方数据
维普
