TY - GEN
T1 - A Multi-source Fused Location Estimation Method for UAV Based on Machine Vision and Strapdown Inertial Navigation
AU - Li, Jiapeng
AU - Shi, Shuo
AU - Gu, Xuemai
N1 - Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2021
Y1 - 2021
N2 - In recent years, unmanned aerial vehicle (UAV) technology has been widely used in industry, agriculture, military and other fields, and its positioning problem has been a research hotspot in this field. To solve the problem of invalidation of integrated navigation of global positioning system (GPS) and strapdown inertial navigation system (SINS) in indoor and other areas, this paper presents a multi-source information fusion location algorithm based on machine vision positioning and SINS. Based on image coordinate system (ICS), body coordinate system (BCS) and navigation coordinate system (NCS), combined with AprilTags recognition and positioning technology, this paper builds NCS with AprilTags array to get the position observation of UAV. Based on the idea of multi-source information fusion, this paper applied third-order fused complementary filter algorithm, which combines with the SINS to obtain accurate three-axis speed and position estimation. Finally, the reliability is verified by the test of the UAV experimental platform.
AB - In recent years, unmanned aerial vehicle (UAV) technology has been widely used in industry, agriculture, military and other fields, and its positioning problem has been a research hotspot in this field. To solve the problem of invalidation of integrated navigation of global positioning system (GPS) and strapdown inertial navigation system (SINS) in indoor and other areas, this paper presents a multi-source information fusion location algorithm based on machine vision positioning and SINS. Based on image coordinate system (ICS), body coordinate system (BCS) and navigation coordinate system (NCS), combined with AprilTags recognition and positioning technology, this paper builds NCS with AprilTags array to get the position observation of UAV. Based on the idea of multi-source information fusion, this paper applied third-order fused complementary filter algorithm, which combines with the SINS to obtain accurate three-axis speed and position estimation. Finally, the reliability is verified by the test of the UAV experimental platform.
KW - Multi-Source information fusion
KW - Strapdown inertial navigation system
KW - Unmanned aerial vehicle
UR - https://www.scopus.com/pages/publications/85104415816
U2 - 10.1007/978-3-030-69066-3_24
DO - 10.1007/978-3-030-69066-3_24
M3 - 会议稿件
AN - SCOPUS:85104415816
SN - 9783030690656
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 272
EP - 282
BT - Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings
A2 - Shi, Shuo
A2 - Ye, Liang
A2 - Zhang, Yu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020
Y2 - 19 December 2020 through 20 December 2020
ER -