Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots
Joint Authors
Yang, Chenguang
Huo, Guanglei
Wang, Ke
Li, Ruifeng
Zhao, Lijun
Wang, Li
Hou, Zhenghua
Luo, Pan
Sun, Zhenye
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-22
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
In order to improve the environmental perception ability of mobile robots during semantic navigation, a three-layer perception framework based on transfer learning is proposed, including a place recognition model, a rotation region recognition model, and a “side” recognition model.
The first model is used to recognize different regions in rooms and corridors, the second one is used to determine where the robot should be rotated, and the third one is used to decide the walking side of corridors or aisles in the room.
Furthermore, the “side” recognition model can also correct the motion of robots in real time, according to which accurate arrival to the specific target is guaranteed.
Moreover, semantic navigation is accomplished using only one sensor (a camera).
Several experiments are conducted in a real indoor environment, demonstrating the effectiveness and robustness of the proposed perception framework.
American Psychological Association (APA)
Wang, Li& Zhao, Lijun& Huo, Guanglei& Li, Ruifeng& Hou, Zhenghua& Luo, Pan…[et al.]. 2018. Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots. Complexity،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132937
Modern Language Association (MLA)
Wang, Li…[et al.]. Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots. Complexity No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1132937
American Medical Association (AMA)
Wang, Li& Zhao, Lijun& Huo, Guanglei& Li, Ruifeng& Hou, Zhenghua& Luo, Pan…[et al.]. Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots. Complexity. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132937
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132937