MARC状态：审校 文献类型：西文图书 浏览次数：30
- 题名/责任者:
- Multimodal perception and secure state estimation for robotic mobility platforms / Xinghua Liu, Rui Jiang, Badong Chen, Shuzhi Sam Ge.
- 出版发行项:
- Hoboken, New Jersey : Wiley, [2023]
- 出版发行项:
- The Institute of Electrical and Electronics Engineers, ?2023
- ISBN:
- 9781119876014
- 载体形态项:
- xvi, 208 pages : illustrations ; 25 cm
- 其他载体形态:
- Online version: Liu, Xinghua (Professor) Multimodal perception and secure state estimation for robotic mobility platforms Hoboken, New Jersey : Wiley-IEEE Press, [2023] 9781119876021
- 个人责任者:
- Liu, Xinghua (Professor), author.
- 附加个人名称:
- Jiang, Rui (Research fellow), author.
- 附加个人名称:
- Chen, Badong, author.
- 附加个人名称:
- Sam Ge, Shuzhi, author.
- 论题主题:
- Multisensor data fusion.
- 论题主题:
- Mobile robots.
- 论题主题:
- Automated vehicles.
- 中图法分类号:
- TP212.9
- 中图法分类号:
- TP242
- 书目附注:
- Includes bibliographical references (pages 189-206) and index.
- 摘要附注:
- "This book provides a novel perspective on secure state estimation and multimodal perception for robotic mobility platforms such as autonomous vehicles. In particular, the book discusses the two essential topics in autonomous systems: 1. secure state estimation that focuses on system robustness under cyber-attacks, and 2. multi-sensor fusion that helps improve system performance based on the complementary characteristics of different sensors. Finally, the authors introduce a geometric pose estimation framework to incorporate measurements and constraints into a unified fusion scheme, where real-time road-constrained and heading-assisted pose estimation is achieved. The proposed geometric pose estimation has been validated using public and self-collected data and can be further extended to other kinds of sensor configurations with state and measurement constraints."--
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