TY - GEN
T1 - OmniNxt
T2 - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
AU - Liu, Peize
AU - Feng, Chen
AU - Xu, Yang
AU - Ning, Yan
AU - Xu, Hao
AU - Shen, Shaojie
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, which limits researchers from utilizing aerial robots with omnidirectional FoV in their research. To bridge this gap, we propose OmniNxt, a fully open-source aerial robotics platform with omnidirectional perception. We design a high-performance flight controller Nxt-FC and a multi-fisheye camera set for OmniNxt. Meanwhile, the compatible software is carefully devised, which empowers OmniNxt to achieve accurate localization and real-time dense mapping with limited computation resource occupancy. We conducted extensive real-world experiments to validate the superior performance of OmniNxt in practical applications. All the hardware and software are open-access at3, and we provide docker images of each crucial module in the proposed system. Project page: https://hkust-aerial-robotics.github.io/OmniNxt.
AB - Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, which limits researchers from utilizing aerial robots with omnidirectional FoV in their research. To bridge this gap, we propose OmniNxt, a fully open-source aerial robotics platform with omnidirectional perception. We design a high-performance flight controller Nxt-FC and a multi-fisheye camera set for OmniNxt. Meanwhile, the compatible software is carefully devised, which empowers OmniNxt to achieve accurate localization and real-time dense mapping with limited computation resource occupancy. We conducted extensive real-world experiments to validate the superior performance of OmniNxt in practical applications. All the hardware and software are open-access at3, and we provide docker images of each crucial module in the proposed system. Project page: https://hkust-aerial-robotics.github.io/OmniNxt.
UR - https://www.scopus.com/pages/publications/85216480474
U2 - 10.1109/IROS58592.2024.10802134
DO - 10.1109/IROS58592.2024.10802134
M3 - 会议稿件
AN - SCOPUS:85216480474
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 10605
EP - 10612
BT - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 October 2024 through 18 October 2024
ER -