Unscented FastSLAM for UAV

摘要：

Simultaneous localization and mapping (SLAM) is a necessary prerequisite to make mobile vehicle truly autonomous, which is a hot research topic today. FastSLAM as a successful SLAM method abstracts many researchers attentions. FastSLAM factors the SLAM problem into a localization problem and a mapping problem in which the landmark position is estimated by EKF. A modified FastSLAM is presented for uninhabited aerial vehicle (UAV), using UKF to replace the EKF to estimate the landmark position. So we can improve the estimation precision, at the same time no need to linearize the sensor observation model and to compute its Jacobian matrix.

关键词： simultaneous localization and mapping (SLAM) unscented Kalman filter (UKF) extend Kalman filter (EKF) FastSLAM uninhabited aerial vehicle

作者: Shi Jianli Wu Yuqiang Pan Shuang Wang Xibin

作者单位: Department of missile weapon Naval Submarine Academy Qingdao, China Department of training Naval Submarine Academy Qingdao, China Department of Control Engineering Naval Aeronautical and Astronautical University Yantai, China

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 2529-2532

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）