Improved Particle Swarm Optimization Algorithm for Robot Obstacle Avoidance Deviation Control
In order to effectively control the obstacle avoidance deviation of inspection robots and improve the obstacle avoidance ef-fect,an improved particle swarm optimization algorithm for robot obstacle avoidance deviation control method design is proposed.Firstly,the forward dynamics and reverse dynamics of the inspection robot are analyzed,and the motion of the robot in the double walking wheel coordinate system is obtained,and the robot kinematics equation is established.Then,based on this,in the dual wheel coordinate system,an improved particle swarm optimization algorithm is used to determine the global optimal path for obstacle avoidance of the inspection robot.The improved artificial potential field method is used to complete local obstacle avoidance path planning.Finally,a feedforward compensation controller is used to establish dynamic compensation for the dynamic equation and optimal path.Based on the training results output by the controller,automatic control of obstacle avoidance deviation of the inspec-tion robot is achieved.The experimental results show that the proposed method has strong obstacle avoidance planning ability and ob-stacle avoidance motion control ability,and good obstacle avoidance deviation control effect,which has certain application value.
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