期刊
MEASUREMENT
卷 71, 期 -, 页码 89-101出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2015.02.026
关键词
Autonomous underwater vehicle; Autonomous navigation and control; FastSLAM; Particle swarm optimization; Unscented particle filter; Unscented Kalman filter
资金
- Natural Science Foundation of China [41176076, 51075377, 51379198]
- High Technology Research and Development Program of China [2006AA09Z231, 2014AA093410]
Simultaneous localization and mapping (SLAM) is the crucial prerequisite for mobile robots to accomplish autonomy. In this paper, PSO-UFastSLAM based on the unscented-FastSLAM (UFastSLAM) and the particle swarm optimization (PSO) is proposed. The UFastSLAM combines unscented particle filter (UPF) and unscented Kalman filter (UKF) to estimate the robot poses and features. Furthermore, to prevent the particles degeneracy and impoverishment, PSO is adapted to optimize particles. The proposed method is applied on our own research platform, autonomous underwater vehicle (AUV), through sea trials in Tuandao Bay. The results of simulation and sea trial reveal that PSO-UFastSLAM has better accuracy and effectiveness in terms of estimation of robot and features while compared with UFastSLAM and standard FastSLAM. (C) 2015 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据