計測自動制御学会論文集
Online ISSN : 1883-8189
Print ISSN : 0453-4654
ISSN-L : 0453-4654
論文
ロボットの横断歩道横断のための深層学習を用いた歩行者用信号機の認識
重松 康祐小西 裕一満留 諒介坪内 孝司
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ジャーナル フリー

2018 年 54 巻 1 号 p. 99-110

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This paper describes recognition of pedestrian traffic light at crosswalk for a mobile robot using deep learning. In order for a robot to cross a crosswalk, the robot needs to recognize the color of the traffic light like a human. A recognition of traffic light by camera images based on manually designed image features is possible. However, it requires significant amount of labor to adjust parameters under changing lighting condition. Therefore, in this paper we tried to recognize traffic lights using deep learning. The proposed method consists of two processes: a detection of traffic light and a classification of a traffic light color using deep learning. These processes can be processed in an allowable time by a small computer mountable on a mobile robot. Through a series of experiments, the proposed method successfully recognizes traffic signal in real environments.

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© 2018 公益社団法人 計測自動制御学会
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