An FLC-Pso Algorithm-Controlled Mobile Robot

Abstract

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied.

A smart guidance navigation robot using petri net, database location, and radio frequency identification

“…Many studies have been conducted on mobile robots with only one goal target control as observed with the use of fuzzy logic [7]- [11], particle swarm optimation [12], odometry [13], the need for precise motor rotation constraint, database using RFID for only one goal target [14]- [19], motion robot [20]- [23], navigation gps [24], merging between PN and RFID for navigation with 1 destination and 4 destinations [25]- [27].…”