The obstacles detection for outdoor robot based on computer vision in deep learning

Hsuan Chen, Wen Hsin Chiu, Jian Cheng Yu, Hsiang Chieh Chen, Wen June Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this thesis, we propose a guided robot with deep learning techniques and machine vision in order to predict distance and avoid obstacles. The training data images are captured by the stereo camera, and output results are disparity of the single image. Then, the distances are converted by using the triangulation method of computer vision. The back propagation neural network retrains to obtain the actual distance of each pixel in the image. Therefore, the robot with the monocular camera could know the distance between obstacles and itself. Semantic segmentation is utilized to a to distinguish road and obstacles in the image. Fuzzy theory for calculating the area of the road which be cut is designed to avoid walking into the intersection. The obstacle depth and the walkable area are taken as an information for avoiding obstacles control. Because of the robot is proposed to walk on the right side along the road, the edge of road is necessary to navigate the robot. The Hough method is used to find the straight line, and then choose the line we need. The path planning is also achieved in through of navigation and obstacle avoidance control. As a result, the robot can arrive the destination safely and precisely.

原文???core.languages.en_GB???
主出版物標題Proceedings - 2019 IEEE 9th International Conference on Consumer Electronics, ICCE-Berlin 2019
編輯Gordan Velikic, Christian Gross
發行者IEEE Computer Society
頁面184-188
頁數5
ISBN(電子)9781728127453
DOIs
出版狀態已出版 - 9月 2019
事件9th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2019 - Berlin, Germany
持續時間: 8 9月 201911 9月 2019

出版系列

名字IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
2019-September
ISSN(列印)2166-6814
ISSN(電子)2166-6822

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???event.eventtypes.event.conference???9th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2019
國家/地區Germany
城市Berlin
期間8/09/1911/09/19

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