TY - GEN
T1 - Distributed UAV Swarm Collaborative SLAM Based on Visual-Inertial-Ranging Measurement
AU - Shou, Yicheng
AU - Song, Zhuoyue
AU - Qi, Haoyu
AU - Li, Zhen
AU - Chen, Wenjie
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Compared with the standalone operation, unmanned aerial vehicle (UAV) swarm systems bring the high efficiency to the task execution in a cooperative manner, and they has gained the widespread application in disaster relief, power inspection and other fields. To support the fulfillment of cooperative task, the cooperative positioning capability plays the key role in global positioning system (GPS) denied areas. However, there are still difficulties in initialization, high communication demand, and inevitable drift for swarm cooperative positioning. In order to solve the problems above, a distributed collaborative simultaneous localization and mapping (SLAM) system is developed based on ranging measurement from ultra-wideband (UWB), which specifically accelerates the initialization by introducing prior information, and optimizes the communication framework between the UAVs so as to run in real time. Besides, the ranging is introduced as the restraints on the relative drift between the nodes. The evaluation are performed on datasets recorded in a lab environment. Experiments results show that our method surpasses 15% over the mainstream visual-inertial odometry in positioning accuracy. Furthermore, our method effectively reduces the drift of the visual-inertial odometry in challenging scenarios on visual.
AB - Compared with the standalone operation, unmanned aerial vehicle (UAV) swarm systems bring the high efficiency to the task execution in a cooperative manner, and they has gained the widespread application in disaster relief, power inspection and other fields. To support the fulfillment of cooperative task, the cooperative positioning capability plays the key role in global positioning system (GPS) denied areas. However, there are still difficulties in initialization, high communication demand, and inevitable drift for swarm cooperative positioning. In order to solve the problems above, a distributed collaborative simultaneous localization and mapping (SLAM) system is developed based on ranging measurement from ultra-wideband (UWB), which specifically accelerates the initialization by introducing prior information, and optimizes the communication framework between the UAVs so as to run in real time. Besides, the ranging is introduced as the restraints on the relative drift between the nodes. The evaluation are performed on datasets recorded in a lab environment. Experiments results show that our method surpasses 15% over the mainstream visual-inertial odometry in positioning accuracy. Furthermore, our method effectively reduces the drift of the visual-inertial odometry in challenging scenarios on visual.
KW - collaborative SLAM
KW - multi-robot system
KW - pose graph optimization
KW - visual-inertial-ranging SLAM
UR - http://www.scopus.com/pages/publications/105001363228
U2 - 10.1007/978-981-96-2220-7_18
DO - 10.1007/978-981-96-2220-7_18
M3 - Conference contribution
AN - SCOPUS:105001363228
SN - 9789819622191
T3 - Lecture Notes in Electrical Engineering
SP - 183
EP - 192
BT - Advances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 6
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Deng, Yimin
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2024
Y2 - 9 August 2024 through 11 August 2024
ER -