TY - GEN
T1 - A Multi-sensor Combined Tracking Method for Following Robots
AU - Liu, Hao
AU - Yu, Gang
AU - Hu, H.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - At present, the research on tracking methods is mainly based on visual tracking algorithm, which has reduced the accuracy at night or under the condition of insufficient light intensity. Therefore, this paper starts from the direction of multi-sensor combined tracking. Firstly, in order to verify the feasibility and performance of the multi-sensor combined tracking method proposed in this paper, a set of tracking robot system is designed. Secondly, aiming at the problem that the visual tracking method fails to track in scenes such as complete occlusion and insufficient illumination, the non-line-of-sight perception of the following target is realized based on the fusion of ultra-wide band (UWB) and inertial measurement unit (IMU) sensors. Besides, based on coordinate transformation and decision tree algorithm, this paper makes decisions on UWB and visual tracking targets to achieve combined tracking.
AB - At present, the research on tracking methods is mainly based on visual tracking algorithm, which has reduced the accuracy at night or under the condition of insufficient light intensity. Therefore, this paper starts from the direction of multi-sensor combined tracking. Firstly, in order to verify the feasibility and performance of the multi-sensor combined tracking method proposed in this paper, a set of tracking robot system is designed. Secondly, aiming at the problem that the visual tracking method fails to track in scenes such as complete occlusion and insufficient illumination, the non-line-of-sight perception of the following target is realized based on the fusion of ultra-wide band (UWB) and inertial measurement unit (IMU) sensors. Besides, based on coordinate transformation and decision tree algorithm, this paper makes decisions on UWB and visual tracking targets to achieve combined tracking.
KW - Following robot
KW - Multi-sensor combined tracking
KW - Target tracking
UR - https://www.scopus.com/pages/publications/85136149621
U2 - 10.1007/978-3-031-13822-5_65
DO - 10.1007/978-3-031-13822-5_65
M3 - 会议稿件
AN - SCOPUS:85136149621
SN - 9783031138218
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 722
EP - 734
BT - Intelligent Robotics and Applications - 15th International Conference, ICIRA 2022, Proceedings
A2 - Liu, Honghai
A2 - Ren, Weihong
A2 - Yin, Zhouping
A2 - Liu, Lianqing
A2 - Jiang, Li
A2 - Gu, Guoying
A2 - Wu, Xinyu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Intelligent Robotics and Applications, ICIRA 2022
Y2 - 1 August 2022 through 3 August 2022
ER -