TY - GEN
T1 - Ultra-wideband aided fast localization and mapping system
AU - Wang, Chen
AU - Zhang, Handuo
AU - Nguyen, Thien Minh
AU - Xie, Lihua
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/13
Y1 - 2017/12/13
N2 - This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces challenges with accumulated errors in the long run or under unfavourable environments, the UWB ranging measurements are fused to remove the visual drift and improve the robustness. A general framework is developed which consists of three parallel threads, two of which carry out the visualinertial odometry (VIO) and UWB localization respectively. The other mapping thread integrates visual tracking constraints into a pose graph with the proposed smooth and virtual range constraints, such that a bundle adjustment is performed to provide robust trajectory estimation. Experiments show that the proposed system is able to create dense drift-free maps in real-time even running on an ultra-low power processor in featureless environments.
AB - This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces challenges with accumulated errors in the long run or under unfavourable environments, the UWB ranging measurements are fused to remove the visual drift and improve the robustness. A general framework is developed which consists of three parallel threads, two of which carry out the visualinertial odometry (VIO) and UWB localization respectively. The other mapping thread integrates visual tracking constraints into a pose graph with the proposed smooth and virtual range constraints, such that a bundle adjustment is performed to provide robust trajectory estimation. Experiments show that the proposed system is able to create dense drift-free maps in real-time even running on an ultra-low power processor in featureless environments.
UR - https://www.scopus.com/pages/publications/85041960217
U2 - 10.1109/IROS.2017.8205968
DO - 10.1109/IROS.2017.8205968
M3 - Conference contribution
AN - SCOPUS:85041960217
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 1602
EP - 1609
BT - IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
Y2 - 24 September 2017 through 28 September 2017
ER -