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• Main Authors: Wen-Hsin Chiu, 邱文欣
• Other Authors: 王文俊
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/ecrck2

碩士 === 國立中央大學 === 電機工程學系 === 107 === This thesis designs and improves the functions of moving guidance and obstacle avoidance for the guided robot from reference[1] such that the robot can be helpful to the blind much more in his/her daily life. First, the user clicks the destination on the cell phone, then the phone can plan the moving path for the robot by using Google map. According to the current position, attitude of the robot and the destination position, the phone will send the navigation command to the computer on the robot. This robot just uses one webcam to capture the image ahead, by using the semantic segmentation method and deep learning network, we can find the accessible road area and predict the disparity of the obstacle ahead of the robot, respectively. Based on the disparity and an inverse function, the depth map of the obstacle is obtained and the distance between the robot and obstacle is estimated from the analysis of the depth histogram. In this study, the distance from 0.8m to 4m can be estimated with 80% accuracy. When the accessible area is obtained, Hough line is created to present the border of the road at the right side of the robot. Let the accessible area of the road ahead of the robot be divided to several rectangular squares. Since the robot is forced to move along the right side of the road, then we can find the trajectory point in each square. By using fuzzy control technique, the speeds of both wheels are adjusted such that the robot can move following the trajectory points. Based on the above distance estimation for obstacles, when the obstacle is on the center of image and its estimated distance is about 3.5 m, the robot will start to avoid the obstacle; but it will stop when the obstacle suddenly appears 1m ahead, then it will move until the obstacle disappears. According to the outdoor experiment in NCU campus, the obstacle distance estimation is more accurate and the robot moving control is much more stable than that in [1] such that the robot can guide the blind reaching the destination safely and accurately.