31 / 2017-05-09 09:12:49

Research on Path Tracking Method of Trackless Robot

13905,PID,BP neural network

Currently indoor intelligent robots are mostly based on rail tracking mode which has low intelligence, simplex movement, inflexibility and independent route planning. In order to get rid of the tracking mode and achieve non-assisted trackless robot free walking control system, the robot must be highly intelligent and autonomously controlled. In this paper, the path tracking process of the trackless robot is analyzed, and a Double closed-loop PID motion Control Model for planning path tracking (DPCM) is established according to its operating characteristics. In addition, the PID parameters of DPCM are tuned by the BP neural network. Through the direction control, the robot has no direction deviation for the planning path. The lateral deviation control is used to implement the robot without lateral deviation to the planning path, thus laying a foundation for the autonomous walking control of the robot. Through the verification of the actual operation of the trackless robot, it proves that DPCM effectively realizes the follow-up control of the trackless robot for the planning path and improves the accuracy of the tracking system as well.