Behavior-based robot navigation using ultrasonic sensor array and neuro-fuzzy techniques

Pao Yue-kong Library Electronic Theses Database

Behavior-based robot navigation using ultrasonic sensor array and neuro-fuzzy techniques

 

Author: Wong, Wing-yu
Title: Behavior-based robot navigation using ultrasonic sensor array and neuro-fuzzy techniques
Degree: M.Phil.
Year: 2003
Subject: Hong Kong Polytechnic University -- Dissertations
Robotics
Autonomous robots
Fuzzy logic
Intelligent control systems
Department: Dept. of Mechanical Engineering
Pages: xiv, 108, 31, 5 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1733088
URI: http://theses.lib.polyu.edu.hk/handle/200/2570
Abstract: A mobile robot that navigates in an environment can avoid the obstacles and direct to the goal. In order to do so, we have developed behavior-based robot navigation in structured environment. Basically, there are five basic motion behaviors. The mobile robot follows the wall on the left side (left wall following), the wall on the right side (right wall following), walks along the mid-line of the corridor (corridor following), performs right angle turns in a U-shaped or dead end environment (right angle turning), and avoids the obstacle and moves towards the goal (obstacle avoidance and goal seeking). Therefore, we implemented five behavior controllers to represent these features and a behavior selector that will command the robot to execute the most appropriate behavior at any location during navigation. Fuzzy logic is first used for each behavior controller. Afterwards, the results of the fuzzy logic controller are used as the training data for the neural network controller. Furthermore, neural network is used to implement the behavior selector. Simulation results showed that our fuzzy logic controller and neural network controller performed satisfactorily and our behavior selector enabled the robot to reach the goal safely in a structured environment. In order to verify our simulation results, we constructed a mobile robot and then we used it to conduct experiments and the results are satisfactory. In conclusion, we have successfully designed five basic behavior controllers using both fuzzy logic and neural network approaches to enable a mobile robot to navigate in a structured environment. We have also designed a behavior selector that can correctly command the robot to execute the appropriate behavior at any location within the structured environment. The simulation results and the experiments that we conducted showed that our behavior-based neuro-fuzzy navigator is effective.

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