Interval Type-2 Fuzzy Inference Research Articles

Global Path Planning and Path-Following for Wheeled Mobile Robot Using a Novel Control Structure Based on a Vision Sensor

This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical real-time model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time mobile robot applications. First, the structure of the proposed algorithm based on the visual information extracted from an overhead camera has been addressed. Then, the classification process of robot position and orientation, target, and obstacles has been addressed. Second, the path planning algorithms’ initial parameters and obstacles-free path coordinates have been determined by visual information extracted from images in real time. In this step, the interval type-2 fuzzy inference (IT2FIS) algorithm and various algorithms used in path planning have been compared and their performances have been analyzed. The third stage handled the path-following process using a novel control structure for keeping up the robot on the generated path. In this step, the proposed approach is compared with fuzzy Type-1/Type-2 and fuzzy-PID control algorithms, and their results have been analyzed statistically. The proposed system has been successfully implemented on several maps. The experimental results show that the developed design is valid in generating collision-free paths efficiently and consistently and able to guide the robot to follow the path in real time.

Gaze-Guided Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logic

Motion control of mobile robots in a cluttered environment with obstacles is an important problem. It is unsatisfactory to control a robot’s motion using traditional control algorithms in a complex environment in real time. Gaze tracking technology has brought an important perspective to this issue. Gaze guided driving a vehicle based on eye movements supply significant features of nature task to realization. This paper presents an intelligent vision-based gaze guided robot control (GGC) platform that uses a user-computer interface based on gaze tracking enables a user to control the motion of a mobile robot using eyes gaze coordinate as inputs to the system. In this paper, an overhead camera, eyes tracking device, a differential drive mobile robot, vision and interval type-2 fuzzy inference (IT2FIS) tools are utilized. The methodology incorporates two basic behaviors; map generation and go-to-goal behavior. Go-to-goal behavior based on an IT2FIS is more soft and steady progress in data processing with uncertainties to generate better performance. The algorithms are implemented in the indoor environment with the presence of obstacles. Experiments and simulation results indicated that intelligent vision-based gaze guided robot control (GGC) system can be successfully applied and the IT2FIS can successfully make operator intention, modulate speed and direction accordingly.