Heading angle estimation using rotating magnetometer for mobile robots under environmental magnetic disturbances
- PDF / 6,294,605 Bytes
- 19 Pages / 595.276 x 790.866 pts Page_size
- 29 Downloads / 133 Views
ORIGINAL RESEARCH PAPER
Heading angle estimation using rotating magnetometer for mobile robots under environmental magnetic disturbances Feng Ye1 · Feng Shi1 · Yizong Lai1 · Xinjie Zhou1 · Kuo Li1 Received: 3 February 2020 / Accepted: 20 July 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The heading angle plays a vital role in the localization and mapping of mobile robots. It is generally obtained by fusing measurements from gyroscope and magnetometer. However, ferromagnetic objects in real-world environments will disturb the magnetic field and will, therefore, cause significant errors in the estimated heading angles. This work proposes a novel method that employs a rotating magnetometer to detect ambient spatial magnetic disturbances and corrects the heading angle. The algorithm is based on the extended Kalman filter (EKF). Firstly, a criterion named spatial disturbance index is defined to characterize the disturbance quantitatively. And then the magnetometer measurement error covariance of the EKF is tuned adaptively according to the proposed criterion, so that a relatively reliable heading angle can be obtained even under strong spatial dynamic magnetic disturbances. In addition, the estimated heading angle can quickly restore to the correct value when the spatial disturbances disappear. The proposed algorithm has the benefit of adjusting the fusing degree of gyroscope and magnetometer adaptively to reject spatial disturbances and avoid the adverse impact of inherent gyroscope drift. The algorithm is evaluated under static and dynamic conditions in real-world indoor/outdoor environments. The results show that our algorithm outperforms the conventional EKF with fixed measurement error covariance and also the algorithm using only gyroscope. Keywords EKF · Heading angle · Magnetic disturbance · Magnetometers · Mobile robots · Sensor fusion
1 Introduction With the increasing cost of labor and the rapid development of the logistics industry, mobile robots are playing an increasingly important role in autonomous warehousing [1, 2]. Localization is one of the key issues of mobile robot techniques and the basic prerequisite for mapping, navigation and mobile manipulation [3]. Mapping-based localization algorithms, also known as simultaneous localization and mapping (SLAM), have become widely used [4, 5]. For mobile robots confined to planar environments, the pose is usually given by three variables, the two location coordinates in the plane and the heading angle (yaw). The heading angle is more critical so far as mapping is concerned [6]. At present, the techniques to obtain the heading angle * Feng Ye [email protected] 1
School of Mechanical and Automotive Engineering, South China University of Technology, Tianhe, Guangzhou 510641, China
include Global Positioning System (GPS) [7], gyroscope [8] and magnetometer [9]. GPS has low update frequency, and its signals are easily obstructed by walls and buildings, which has low accuracy and may lead to navigation errors. It is suitable
Data Loading...
