TY - GEN
T1 - Tight Fusion of Odometry and Kinematic Constraints for Multiple Aerial Vehicles in Physical Interconnection
AU - Fan, Yingjun
AU - Shi, Chuanbeibei
AU - Lai, Ganghua
AU - Zhang, Ruiheng
AU - Yu, Yushu
AU - Sun, Fuchun
AU - Dong, Yiqun
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Integrated aerial Platforms (IAPs), comprising multiple aircrafts, are typically fully actuated and hold significant potential for aerial manipulation tasks. Differing from a multiple aerial swarm, the aircrafts within the IAP are interconnected, presenting promising opportunities for enhancing localization. Incorporating the physical constraints of these multiple aircrafts to improve the accuracy and reliability of integrated aircraft positioning and navigation systems is a challenging yet highly significant problem. In this paper, we introduce a distributed multi-aircraft visual-inertial-range odometry system that analyzes the position, velocity, and attitude constraints within the IAP. Leveraging constraint relationships in the IAP, we propose corresponding methods that tightly fuse visual-inertial-range odometry and kinematic constraints to optimize odometry accuracy. Our system's performance is validated using a collected dataset, resulting in a notable 28.7% reduction in drift compared to the baseline.
AB - Integrated aerial Platforms (IAPs), comprising multiple aircrafts, are typically fully actuated and hold significant potential for aerial manipulation tasks. Differing from a multiple aerial swarm, the aircrafts within the IAP are interconnected, presenting promising opportunities for enhancing localization. Incorporating the physical constraints of these multiple aircrafts to improve the accuracy and reliability of integrated aircraft positioning and navigation systems is a challenging yet highly significant problem. In this paper, we introduce a distributed multi-aircraft visual-inertial-range odometry system that analyzes the position, velocity, and attitude constraints within the IAP. Leveraging constraint relationships in the IAP, we propose corresponding methods that tightly fuse visual-inertial-range odometry and kinematic constraints to optimize odometry accuracy. Our system's performance is validated using a collected dataset, resulting in a notable 28.7% reduction in drift compared to the baseline.
UR - http://www.scopus.com/inward/record.url?scp=85202431541&partnerID=8YFLogxK
U2 - 10.1109/ICRA57147.2024.10610282
DO - 10.1109/ICRA57147.2024.10610282
M3 - Conference contribution
AN - SCOPUS:85202431541
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3891
EP - 3897
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -