A Real-time relative probabilistic mapping algorithm for high-speed off-road autonomous driving

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	A Real-time relative probabilistic mapping algorithm for high-speed off-road autonomous driving
	Chen C(陈成); He YQ(何玉庆); Gu F(谷丰); Bu CG(卜春光); Han JD(韩建达)
作者部门	机器人学研究室
会议名称	2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
会议日期	September 28 - October 2, 2015
会议地点	Hamburg, Germany
会议录名称	2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
出版者	IEEE
出版地	Piscataway, NJ, USA
	2015
页码	6252-6258
收录类别	EI ; CPCI（ISTP）
EI收录号	20160801970661
WOS记录号	WOS:000371885406056
产权排序	1
ISBN号	978-1-4799-9994-1
摘要	Reliable mapping and hazard detection are prerequisites for autonomous navigation for unmanned ground vehicles. Because of the uncertainty and vibration induced by high-speed navigation and rugged terrain, the problem of mapping for high-speed off-road autonomous navigation has not been completely solved yet. A relative probabilistic mapping (RPM) algorithm is introduced to address the problem. Firstly, the relative probabilistic map is updated by Kalman filter and Gaussian Mixture algorithm based on the probabilistic exteroceptive measurements model. Then, terrain traversability is evaluated to identify obstacles in the map. Experiments on off-road high-speed autonomous vehicle, which suffers from severe vibration, with different sensor configurations are carried out to demonstrate the capability of the RPM algorithm.
语种	英语
引用统计
文献类型	会议论文
条目标识符	http://ir.sia.cn/handle/173321/17459
专题	机器人学研究室
作者单位	1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Acad. of Sci. and Intelligent Driving Technology Research, Research and Advanced Technology, SAIC Motor Corporation Ltd., Beijing, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式 GB/T 7714	Chen C,He YQ,Gu F,et al. A Real-time relative probabilistic mapping algorithm for high-speed off-road autonomous driving[C]. Piscataway, NJ, USA:IEEE,2015:6252-6258.

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