GR-SLAM: Vision-Based Sensor Fusion SLAM for Ground Robots on Complex Terrain
文献类型：会议论文
| 作者 | Su Y(苏赟)2,3,4; Wang T(王挺)2,3 ; Yao C(姚辰)2,3; Shao SL(邵士亮)2,3; Wang, ZD(王志东)1
|
| 出版日期 | 2020 |
| 会议日期 | October 25-29, 2020 |
| 会议地点 | Las Vegas, NV, USA |
| 页码 | 5096-5103 |
| 英文摘要 | In recent years, many excellent SLAM methods based on cameras, especially the camera-IMU fusion (VIO), have emerged, which has greatly improved the accuracy and robustness of SLAM. However, we find through experiments that most of the existing VIO methods perform well on drones or drone datasets, but for ground robots on complex terrain, they cannot continuously provide accurate and robust localization results. Some researchers have proposed methods for ground robots, but most of them have limited applications due to the assumption of plane motion. Therefore, this paper proposes GR-SLAM for the localization of ground robots on complex terrain, which can fuse camera, IMU, and encoder data in a tightly coupled scheme to provide accurate and robust state estimation for robots. First, an odometer increment model is proposed, which can fuse the encoder and IMU data to calculate the robot pose increment on manifold, and calculate the frame constraints through the pre-integrated increment. Then we propose an evaluation algorithm for multi-sensor measurements, which can detect abnormal data and adjust its optimization weight. Finally, we implement a complete factor graph optimization framework based on sliding window, which can tightly couple camera, IMU, and encoder data to perform state estimation. Extensive experiments are conducted based on a real ground robot and the results show that GR-SLAM can provide accurate and robust state estimation for ground robots. |
| 产权排序 | 1 |
| 会议录 | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-6211-9 |
| WOS记录号 | WOS:000714033802130 |
| 源URL | [http://ir.sia.cn/handle/173321/27968]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Su Y(苏赟) |
| 作者单位 | 1.Department of Advanced Robotics, Chiba Institute of Technology, Chiba, Japan. 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 4.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Su Y,Wang T,Yao C,et al. GR-SLAM: Vision-Based Sensor Fusion SLAM for Ground Robots on Complex Terrain[C]. 见:. Las Vegas, NV, USA. October 25-29, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。