Invariant EKF Based Mobile Robot Simultaneous Localization and Mapping Navigation

被引：0
|
作者：
Gu, Chaoyue [1 ]
Sun, Zhenxing [1 ]
Ting, Wang [1 ]
机构：
[1] Nanjing Tech Univ, Coll Elect Engn & Control Sci, Nanjing 211816, Peoples R China
来源：
ARTIFICIAL INTELLIGENCE AND ROBOTICS, ISAIR 2022, PT I | 2022年 / 1700卷
关键词：
Mobile robot; Simultaneous Localization and Mapping; Invariant; Extended Kalman Filter; SLAM;
D O I：
10.1007/978-981-19-7946-0_35
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As robots suffered from magnetic field disturbances, they cannot use satellite navigation such as Global Positioning System to explore the wide unknown area. In this situation, the Simultaneous Localization and Mapping is an efficient choice to obtain the global map by sensors or visions. However, it is inevitable including noises and other disturbances. In this paper, we proposed an Invariant Extended Kalman Filter (IEKF) based navigation method for single mobile robot. The proposed method is simulated on MATLAB platform. Results show good performances of proposed method.
引用
收藏
页码：420 / 426
页数：7
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