|Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization
Jyun-Yu Jhang, Cheng-Jian Lin*, Chin-Teng Lin, and Kuu-Young Young
International Journal of Control, Automation, and Systems, vol. 16, no. 5, pp.2446-2457, 2018
Abstract : "This paper presents an effective navigation control method for mobile robots in an unknown environment.
The proposed behavior manager (BM) switches between two behavioral control patterns, wall-following behavior
(WFB) and toward-goal behavior (TGB), based on the relationship between the mobile robot and the unknown environment.
An interval type-2 fuzzy neural controller with a dynamic-group particle swarm optimization (DGPSO)
algorithm is proposed to provide WFB control and obstacle avoidance for mobile robots. In the WFB learning
process, the input signal of a controller is the distance between the wall and the sonar sensors, and its output signal
is the speed of two wheels of a mobile robot. A fitness function, which operates on the total distance traveled by
the mobile robot, distance from the side wall, angle to the side wall, and moving speed, evaluates the WFB performance
of the mobile robot. In addition, an escape mechanism is proposed to avoid a dead cycle. Experimental
results reveal that the proposed DGPSO is superior to other methods in WFB and navigation control."
"Mobile robot, navigation control, particle swarm optimization, type-2 fuzzy neural controller, wallfollowing control."