Knowledge Commons of Institute of Automation,CAS
ULSM: Underground Localization and Semantic Mapping with Salient Region Loop Closure under Perceptually-Degraded Environment | |
Junhui Wang1![]() ![]() ![]() ![]() | |
2022 | |
会议名称 | IEEE/RSJ International Conference on Intelligent Robots and Systems |
会议日期 | 2022.10.23 |
会议地点 | Kyoto, Japan |
摘要 | Simultaneous Localization and Mapping (SLAM) has been of great assistance to explore perceptually-degraded underground environments, such as human-made tunnel, mine tunnel and cave. However, the recurring sensor failures and spurious loop closures in these scenes brings great challenges to the application of SLAM. In this paper, an architecture for underground localization and semantic mapping (ULSM) is proposed, that promotes the robustness and real-time character of odometry estimation and map-building. In this architecture, a two-stage robust motion compensation with sensor fusion is proposed to adapt sensor-failure situations. The proposed salient region loop closure detection contributes to avoid spurious loop closures. Meanwhile, 3D pose as the initial value for point cloud registration is estimated without additional input. We also design a multi-robot cooperative mapping scheme based on descriptors of salient region. Extensive experiments are conducted on datasets that are collected in Tunnel Circuit of DARPA Subterranean Challenge. |
收录类别 | EI |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 先进智能应用与转化 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51643 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Bin Tian |
作者单位 | 1.中国科学院自动化研究所 2.北京慧拓无限科技有限公司 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Junhui Wang,Bin Tian,Rui Zhang,et al. ULSM: Underground Localization and Semantic Mapping with Salient Region Loop Closure under Perceptually-Degraded Environment[C],2022. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
76122-0949.pdf(2597KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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