Sensor Fusion-Based UAV Localization System for Low-Cost Autonomous Inspection in Extremely Confined Environments
Beiya Yang, Erfu Yang, Leijian Yu, Cong Niu
Abstract
Utilising the unmanned aerial vehicle (UAV) for autonomous inspection in extremely confined environments has become a much sought research area, due to the pressing industrial needs. To provide the high accuracy position information of UAV in such environments, the ultra-wideband (UWB) based localisation technology has been one of the ideal candidates. However, the unpredictable propagation condition and the geomagnetic disturbances for inertial measurement unit (IMU) will all have huge impact on the positioning performance with the single UWB and the IMU/UWB based loosely coupled (LC) sensor fusion approach. Therefore, a tightly coupled adaptive extended Kalman filter (TC-AEKF) based sensor fusion UAV localisation system is proposed and developed in this paper for autonomous inspection in extremely confined environments. The proposed system can attain high accuracy localisation of UAV with 0.097m median error, 0.167m 95 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> percentile error and 0.039m average standard deviation (STD). The drift led by the geomagnetic disturbances for IMU is greatly reduced with the estimation error of the roll, pitch and yaw angle to be 2.15°, 1.54° and 4.58°, respectively. Finally, an autonomous inspection experiment has been conducted to prove the effectiveness of the proposed system and algorithm for actual application, the video from it has been attached in URL https://youtu.be/nEgvwbIVRRk.