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ShanghaiTech University Knowledge Management System
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles | |
2020-05-01 | |
会议录名称 | PROCEEDINGS - IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION |
ISSN | 1050-4729 |
页码 | 2696-2702 |
发表状态 | 已发表 |
DOI | 10.1109/ICRA40945.2020.9196595 |
摘要 | The motion of planar ground vehicles is often non-holonomic, and as a result may be modelled by the 2 DoF Ackermann steering model. We analyse the feasibility of estimating such motion with a downward facing camera that exerts fronto-parallel motion with respect to the ground plane. This turns the motion estimation into a simple image registration problem in which we only have to identify a 2-parameter planar homography. However, one difficulty that arises from this setup is that ground-plane features are indistinctive and thus hard to match between successive views. We encountered this difficulty by introducing the first globally-optimal, correspondence-less solution to plane-based Ackermann motion estimation. The solution relies on the branch-and-bound optimisation technique. Through the low-dimensional parametrisation, a derivation of tight bounds, and an efficient implementation, we demonstrate how this technique is eventually amenable to accurate real-time motion estimation. We prove its property of global optimality and analyse the impact of assuming a locally constant centre of rotation. Our results on real data finally demonstrate a significant advantage over the more traditional, correspondence-based hypothesise-and-test schemes. © 2020 IEEE. |
会议录编者/会议主办者 | IEEE |
关键词 | Intelligent robots Branch and bound method Computer vision Ground vehicles Ackermann steering Efficient implementation Global optimality Optimisation techniques Planar homography Real time motion estimation Registration problems Visual odometry |
会议名称 | 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 |
出版地 | NEW YORK |
会议地点 | Paris, France |
会议日期 | May 31, 2020 - August 31, 2020 |
URL | 查看原文 |
收录类别 | EI ; CPCI-S |
语种 | 英语 |
WOS研究方向 | Automation & Control Systems ; Engineering ; Robotics |
WOS类目 | Automation & Control Systems ; Engineering, Electrical & Electronic ; Robotics |
WOS记录号 | WOS:000712319502002 |
出版者 | Institute of Electrical and Electronics Engineers Inc., United States |
EI入藏号 | 20204309375278 |
EI主题词 | Motion estimation |
EISSN | 2577-087X |
EI分类号 | 723.5 Computer Applications ; 731.6 Robot Applications ; 741.2 Vision ; 921.5 Optimization Techniques |
原始文献类型 | Conference article (CA) |
来源库 | IEEE |
引用统计 | 正在获取...
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文献类型 | 会议论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/251839 |
专题 | 信息科学与技术学院 信息科学与技术学院_PI研究组_Laurent Kneip组 信息科学与技术学院_本科生 信息科学与技术学院_博士生 |
作者单位 | School of School of Information Science and Technology, ShanghaiTech University |
第一作者单位 | 信息科学与技术学院 |
第一作者的第一单位 | 信息科学与技术学院 |
推荐引用方式 GB/T 7714 | Ling Gao,Junyan Su,Jiadi Cui,et al. Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles[C]//IEEE. NEW YORK:Institute of Electrical and Electronics Engineers Inc., United States,2020:2696-2702. |
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