Affiliations: [a] School of Mathematics and Information Engineering, Puyang Institute of Engineering, Henan University, Puyang, China
| [b] Univ Cent Punjab, Sch Business, Lahore, Pakistan
Correspondence:
[*]
Corresponding author. Xiangfen Ma, School of Mathematics and Information Engineering, Puyang Institute of Engineering, Henan University, Puyang, 457000, China. E-mail: [email protected].
Abstract: At present, obstacle avoidance systems of robots cannot avoid obstacles with high efficiency, high stability and high precision. Thus, a self-adaptive obstacle avoidance fuzzy system for mobile robots based on ultrasonic range measurement is proposed and designed. An upper computer, a motor drive module, an ultrasonic ranging sensor module, an infrared sensor module, an electronic compass module, a communication module, a power supply module and peripheral circuits are connected to form the system hardware. After the system is initialized, the robot starts to work according to instructions of the upper computer and enters the self-adaptive obstacle avoidance subroutine. In the subroutine, the ultrasonic sensor scans the infrared sensor output at the corresponding position. After receiving reflection information of the ultrasonic wave, the counter is stopped, and reflection time of the ultrasonic wave is simply calculated and cached into the buffer, so as to determine whether there is an obstacle in front, and the result is fed back to the upper computer through the RS485 bus. If there is an obstacle, then the interrupt program will be called, and the electronic compass program is utilized to determine the direction to avoid the obstacle; if there is no obstacle, the robot will continue to move following instructions of the upper computer to complete the system software design. Experiments show that the average time to avoid obstacles using this system is 0.40 s, and the obstacle avoidance accuracy is high and the stability is good. Under the data comparison and analysis, the proposed system is obviously superior to current systems in the time-consuming and accuracy of obstacle avoidance, and has great reliability.
Keywords: Mobile robots, self-adaptive, obstacle avoidance, system
