A Robot Obstacle Avoidance Method Using Merged CNN Framework

Nai Hsiang Chang, Yi Hsing Chien, Hsin Han Chiang, Wei Yen Wang, Chen Chien Hsu

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

In this paper, a merged convolution neural network (CNN) framework is proposed to automatically avoid obstacles. Although there are many methods for avoiding obstacles, previous methods mostly contain high energy-consuming and high cost. This paper aims to realize an image-based method with a monocular webcam. The experimental results illustrate that the proposed method can effectively avoid obstacles in mobile robot navigation.

原文英語
主出版物標題Proceedings of 2019 International Conference on Machine Learning and Cybernetics, ICMLC 2019
發行者IEEE Computer Society
ISBN(電子)9781728128160
DOIs
出版狀態已發佈 - 2019 七月
事件18th International Conference on Machine Learning and Cybernetics, ICMLC 2019 - Kobe, 日本
持續時間: 2019 七月 72019 七月 10

出版系列

名字Proceedings - International Conference on Machine Learning and Cybernetics
2019-July
ISSN(列印)2160-133X
ISSN(電子)2160-1348

會議

會議18th International Conference on Machine Learning and Cybernetics, ICMLC 2019
國家日本
城市Kobe
期間19/7/719/7/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

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