| Title: | OS11-8 Research on Semantic Map Establishment of Parking Lot Based on Deep Learning and Multi-sensor |
|---|---|
| Publication: | ICAROB2020 |
| Volume: | 25 |
| Pages: | 564-567 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2020.OS11-8 |
| Author(s): | Shiqian Zhang, Yizhun Peng, Ruixiang Bai, Yuheng Zhang, Tianye Jian |
| Publication Date: | January 13, 2020 |
| Keywords: | SLAM, Lidar, RGB-D, Deep learning, Semantic map, ROS, Gazebo |
| Abstract: | With the continuous development of robot technology, SLAM, which is one of the key technologies to realize fully autonomous mobile robots, has become a hot topic in the scientific community. Traditional SLAM technology relies on a single type of sensor to obtain information, and the semantic information of the map is rarely obtained. This paper mainly improves the SLAM mapping technology of the parking lot from the information fusion of sensors and the deep semantics of obtaining map semantic information. Through the lidar and RGB-D camera to obtain multi-modal information, combined with deep learning, extract the semantic information such as the parking lot number and parking position in the image information, help the robot to map and locate faster and better. Finally, simulations were performed using ROS and gazebo to verify the feasibility of the system. |
| PDF File: | https://alife-robotics.co.jp/members2020/icarob/data/html/data/OS/OS11/OS11-8.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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