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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
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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
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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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