Command Fusion Based Fuzzy Controller Design for Moving Obstacle Avoidance of Mobile Robot

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

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Autonomous system to control a mobile robot

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v9i4.2380 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1711-1717

Author(s):

Ayman Abu Baker ◽

Yazeed Yasin Ghadi

Keyword(s):

Mobile Robot ◽

Obstacle Avoidance ◽

Autonomous Navigation ◽

Fuzzy Controller ◽

Computational Time ◽

Ongoing Effort ◽

Unstructured Environment ◽

Adaptive Inference ◽

Real Time Applications ◽

Linguistic Labels

This paper presents an ongoing effort to control a mobile robot in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.

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Machine vision system, robot hardware design and fuzzy controller design for autonomous multi-agent mobile robot platform

2015 International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM) ◽

10.1109/hnicem.2015.7393250 ◽

2015 ◽

Author(s):

Reiner Jan C. Saclolo ◽

Jellie B. Delos Reyes ◽

Nagel Nino Romher B. Formeloza ◽

Jaisel Iris O. Abaca ◽

Kanny Krizzy Serrano ◽

...

Keyword(s):

Machine Vision ◽

Mobile Robot ◽

Fuzzy Controller ◽

Controller Design ◽

Vision System ◽

Hardware Design ◽

Machine Vision System ◽

Multi Agent ◽

Robot Platform

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Expert Fuzzy-Neuro Controller Design for Wall Climbing Robot for Decontamination of Nuclear-Power Station

Journal of Robotics and Mechatronics ◽

10.20965/jrm.1995.p0075 ◽

1995 ◽

Vol 7 (1) ◽

pp. 75-85

Author(s):

Sergei V. Ulyanov ◽

◽

Kazuo Yamafuji ◽

Valery G. Gradetsky ◽

Andrea Pagni ◽

...

Keyword(s):

Mobile Robot ◽

Nuclear Power Station ◽

Nuclear Power ◽

Fuzzy Controller ◽

Controller Design ◽

Horizontal Displacement ◽

Experimental Investigations ◽

Climbing Robot ◽

Power Station ◽

Environment Recognition

The arrangement principles and design methodology for complex control framework of Al control systems are introduced. The notions of intelligence levels with top boundary (""intelligence in large"") and the bottom boundary (""intelligence in small"") are defined. Special methodology of Al control system design for decontamination of nuclear-power station (IMPS) on the base of a wall-climbing robot (WCR) with various intelligence levels is considered. The basis of this methodology is computer simulation of dynamics for mechanical systems with the help of qualitative physics and search for possible solutions by genetic algorithm (GA). On artificial neural networks, optimal solutions are obtained and a knowledge base of fuzzy controller on WARP (Weight Associative Rule Processor) is formed. Strategy for planning, environment recognition using two types of sensors, and locomotion control to realize autonomous locomotion of the mobile robot are described. The WCR and the mobile robot for horizontal displacement with manipulators are moved in unstructured environments. Fuzzy qualitative simulation, GA and hierarchical node map, and fuzzy neural network (FNN) have demonstrated their effectiveness for path planning of the mobile robots. The results of fuzzy robot control simulation, monitoring, and experimental investigations are presented. The application of WARP to design automatic fuzzy controller for fuzzy correction motion of manipulator and WCR is examined.

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