TY - GEN
T1 - An IMU-Only Attitude Solution and SLAM Loosely Coupled System for UAV Localization in Camera-Failure Scenarios during Nuclear Rescues
AU - Chen, Yuqiang
AU - Peng, Zhihong
AU - Li, Yukun
AU - Shan, Shilei
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In search and rescue missions, UAV localization largely relies on visual-inertial SLAM methods, whose accuracy depends on image quality. However, in nuclear accident scenarios, high-energy particles can damage the camera’s photosensitive elements, leading to the loss of camera images in the most severe case. This paper proposes an IMU-only attitude solution and SLAM loosely coupled system for auxiliary UAV localization when the camera fails. The system employs a two-step complementary filter for the IMU-only attitude solution, and optimizes the reinitialization process of the open-source SLAM system Vins-Fusion to ensure rapid switching between these two threads. To ensure the accuracy of the IMU-only attitude solution, a low-pass filter is used for gyroscope bias compensation, a state machine is employed for magnetic interference resistance, and the fourth-order Runge-Kutta method is utilized for position estimation. Experimental results show that the algorithm can accurately and stably localize the UAV when the camera fails.
AB - In search and rescue missions, UAV localization largely relies on visual-inertial SLAM methods, whose accuracy depends on image quality. However, in nuclear accident scenarios, high-energy particles can damage the camera’s photosensitive elements, leading to the loss of camera images in the most severe case. This paper proposes an IMU-only attitude solution and SLAM loosely coupled system for auxiliary UAV localization when the camera fails. The system employs a two-step complementary filter for the IMU-only attitude solution, and optimizes the reinitialization process of the open-source SLAM system Vins-Fusion to ensure rapid switching between these two threads. To ensure the accuracy of the IMU-only attitude solution, a low-pass filter is used for gyroscope bias compensation, a state machine is employed for magnetic interference resistance, and the fourth-order Runge-Kutta method is utilized for position estimation. Experimental results show that the algorithm can accurately and stably localize the UAV when the camera fails.
KW - IMU attitude solution
KW - magnetic interference resistance
KW - SLAM
KW - UAV localization
UR - http://www.scopus.com/inward/record.url?scp=86000723727&partnerID=8YFLogxK
U2 - 10.1109/CAC63892.2024.10864782
DO - 10.1109/CAC63892.2024.10864782
M3 - Conference contribution
AN - SCOPUS:86000723727
T3 - Proceedings - 2024 China Automation Congress, CAC 2024
SP - 2306
EP - 2311
BT - Proceedings - 2024 China Automation Congress, CAC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 China Automation Congress, CAC 2024
Y2 - 1 November 2024 through 3 November 2024
ER -