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  4. Sensor Fusion and Control System Design for an Unmanned Vehicle
 
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Sensor Fusion and Control System Design for an Unmanned Vehicle

Date Issued
2010
Date
2010
Author(s)
Su, Shuan-Yi
URI
http://ntur.lib.ntu.edu.tw//handle/246246/250119
Abstract
The objective of this research is to integrate GPS receiver, inertial navigation system(INS), electronic compass, stereo camera, and ultrasonic range sensors to develop an outdoor unmanned vehicle system. The developed system consists of three parts : the main station, the reference station, and the unmanned vehicle. The position of the unmanned vehicle is provided by GPS with triple difference carrier phase method. The INS, with its high data rate, is integrated with GPS to increase the positioning rate. With the attitude angle which is obtained from electronic compass and the position of the vehicle, the unmanned vehicle is able to track the reference path by a fuzzy controller. The obstacles in front of the vehicle can be detected by the stereo camera by using the principle of plane induced parallax. The position and distance of the obstacles with respect to the unmanned vehicle can be determined by the method of stereo triangulation. The waypoints around the obstacle are then selected. With the information of the position of the destination, the unmanned vehicle will choose the shorter path through the waypoints to avoid the obstacles and reach the destination point. The unmanned vehicle is also equipped with six ultrasonic range sensors to detect the obstacle around it. With the help of ultrasonic sensors, the unmanned vehicle can avoid the collision with the moving obstacles in real time. Using various obstacle-avoidance modes and the goal-approaching mode, the unmanned vehicle can reach the destination point without the collision with the surrounding obstacles. The experimental results show that the proposed integration and control methodologies are feasible.
Subjects
Unmanned vehicle
Stereo vision
Plane induced parallax
Stereo triangulation
Inertial navigation system
Global positioning system
Kalman filter
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