TY - GEN
T1 - A Centralized Cooperative SLAM System for Improving Positioning and Perception Accuracy in GPS-Denied Environments
AU - Li, Xiaotian
AU - Wang, Zhengjie
AU - Tan, Yunfei
AU - Zhang, Xiaoning
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - One of the key points in robotic collaboration is localization. In some scenarios where the Global Navigation Satellite System (GNSS) signal is unavailable, robots must rely on their own sensors for environment perception and self-localization. Simultaneous Localization And Mapping (SLAM) technology, as a widely used method for perceiving the external environment, has been extensively applied in the field of robotics. The existing work faced problems with scalability, robustness, and data association inaccuracies, and therefore this paper developed a collaborative vision SLAM algorithm for multi-robots. The proposed system, based on a centralized collaborative architecture, adopts a centralized collaborative architecture, including a central node and several sub-nodes. We also conducted simulations and experiments on homogeneous and heterogeneous platforms, demonstrating that the system can perform high-efficiency and high-precision positional perception in indoor and outdoor environments.
AB - One of the key points in robotic collaboration is localization. In some scenarios where the Global Navigation Satellite System (GNSS) signal is unavailable, robots must rely on their own sensors for environment perception and self-localization. Simultaneous Localization And Mapping (SLAM) technology, as a widely used method for perceiving the external environment, has been extensively applied in the field of robotics. The existing work faced problems with scalability, robustness, and data association inaccuracies, and therefore this paper developed a collaborative vision SLAM algorithm for multi-robots. The proposed system, based on a centralized collaborative architecture, adopts a centralized collaborative architecture, including a central node and several sub-nodes. We also conducted simulations and experiments on homogeneous and heterogeneous platforms, demonstrating that the system can perform high-efficiency and high-precision positional perception in indoor and outdoor environments.
KW - centralized architecture
KW - collaborative localization and mapping
KW - visual SLAM
UR - http://www.scopus.com/inward/record.url?scp=85180123459&partnerID=8YFLogxK
U2 - 10.1109/ICUS58632.2023.10318269
DO - 10.1109/ICUS58632.2023.10318269
M3 - Conference contribution
AN - SCOPUS:85180123459
T3 - Proceedings of 2023 IEEE International Conference on Unmanned Systems, ICUS 2023
SP - 812
EP - 817
BT - Proceedings of 2023 IEEE International Conference on Unmanned Systems, ICUS 2023
A2 - Song, Rong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Unmanned Systems, ICUS 2023
Y2 - 13 October 2023 through 15 October 2023
ER -