Machine vision based sliding fuzzy-PDC control for obstacle avoidance and object recognition of service robot platform

Article type: Research Article

Authors: Mon, Yi-Jen

Affiliations: Department of Computer Science and Information Engineering, Taoyuan Innovation Institute of Technology, Chung-Li, Taoyuan, Taiwan, R. O. C.

Note: [] Corresponding author. Yi-Jen Mon, Department of Computer Science and Information Engineering, Taoyuan Innovation Institute of Technology, No. 414, Sec. 3, Chung-Shang East Rd., Chung-Li, Taoyuan, 320, Taiwan, R. O. C. Tel.: +886 3 4361070 6937; Fax: +886 4361070 6999; E-mail: monbuy@tiit.edu.tw

Abstract: This paper develops a machine vision based design method of sliding fuzzy PDC (parallel distributed compensation) controller applied to deal with obstacle avoidance and target approaching for service robot platform. Some ultrasound sensors and camera are used to get the data of surround obstacles then a new sliding surface vector based on the fuzzy-PDC concept is defined. The Lyapunov stability condition is guaranteed in this design to develop strictly robust sliding fuzzy-PDC control. The simulation results and empirical test of this controller demonstrate that the performance and robustness are satisfied.

Keywords: Robot, machine vision, sliding mode, fuzzy-PDC, obstacle avoidance

DOI: 10.3233/IFS-141395

Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 3, pp. 1119-1126, 2015