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Multi-Robot Obstacle Avoidance Based on the Improved Artificial Potential Field and PID Adaptive Tracking Control Algorithm

Published online by Cambridge University Press:  16 April 2019

Zhenhua Pan ,
Dongfang Li ,
Kun Yang  and
Hongbin Deng
Zhenhua Pan
Affiliation:
Department of Electromechanical Engineering, Beijing Institute of Technology, Beijing, China. E-mails: [email protected], [email protected], [email protected]
Dongfang Li
Affiliation:
Department of Electromechanical Engineering, Beijing Institute of Technology, Beijing, China. E-mails: [email protected], [email protected], [email protected]
Kun Yang
Affiliation:
Department of Electromechanical Engineering, Beijing Institute of Technology, Beijing, China. E-mails: [email protected], [email protected], [email protected]
Hongbin Deng*
Affiliation:
Department of Electromechanical Engineering, Beijing Institute of Technology, Beijing, China. E-mails: [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

As for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

Keywords

Multi-robotIAPFObstacle avoidanceMSAMFormation control
Type
Articles
Information
Robotica , Volume 37 , Issue 11 , November 2019 , pp. 1883 - 1903
Copyright
© Cambridge University Press 2019 

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