Marker-based multi-sensor fusion indoor localization system for micro air vehicles

Boyang Xing, Quanmin Zhu, Feng Pan, Xiaoxue Feng*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

34 引用 (Scopus)

摘要

A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

源语言英语
文章编号1706
期刊Sensors
18
6
DOI
出版状态已出版 - 6月 2018

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引用此

Xing, B., Zhu, Q., Pan, F., & Feng, X. (2018). Marker-based multi-sensor fusion indoor localization system for micro air vehicles. Sensors, 18(6), 文章 1706. https://doi.org/10.3390/s18061706