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Open AccessArticle

Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles

School of Automation, Beijing Institute of Technology, Beijing 100081, China
Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol BS16 1QY, UK
Kunming-BIT Industry Technology Research Institute INC, Kunming 650106, China
Author to whom correspondence should be addressed.
Sensors 2018, 18(6), 1706;
Received: 3 April 2018 / Revised: 16 May 2018 / Accepted: 22 May 2018 / Published: 25 May 2018
(This article belongs to the Section Sensor Networks)
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. View Full-Text
Keywords: indoor localization; ArUco marker; federated filter; Micro Aerial Vehicle indoor localization; ArUco marker; federated filter; Micro Aerial Vehicle
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Xing, B.; Zhu, Q.; Pan, F.; Feng, X. Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles. Sensors 2018, 18, 1706.

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