TY - GEN
T1 - Multi-sensor fusion based obstacle localization technology
AU - Lyu, Kejing
AU - Hu, Jinwen
AU - Zhao, Chunhui
AU - Hou, Xiaolei
AU - Xu, Zhao
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/9
Y1 - 2020/10/9
N2 - Multi-sensor fusion has become a fundamental and important problem in 3D obstacle localization technology. In this paper, an obstacle localization method based on lidar and camera fusion for resampling in missed area is presented. The depth value of unknown area is estimated by fusing neighborhood information. At the same time, the uncertainty of the estimated point is calculated to determine the sampling point at the next step. Then we calculate the gimbal rotation angle to resample the missed detection area. Finally we vertify the results experimentally, showing the adaptability of our method.
AB - Multi-sensor fusion has become a fundamental and important problem in 3D obstacle localization technology. In this paper, an obstacle localization method based on lidar and camera fusion for resampling in missed area is presented. The depth value of unknown area is estimated by fusing neighborhood information. At the same time, the uncertainty of the estimated point is calculated to determine the sampling point at the next step. Then we calculate the gimbal rotation angle to resample the missed detection area. Finally we vertify the results experimentally, showing the adaptability of our method.
UR - http://www.scopus.com/inward/record.url?scp=85098063083&partnerID=8YFLogxK
U2 - 10.1109/ICCA51439.2020.9264419
DO - 10.1109/ICCA51439.2020.9264419
M3 - 会议稿件
AN - SCOPUS:85098063083
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 731
EP - 736
BT - 2020 IEEE 16th International Conference on Control and Automation, ICCA 2020
PB - IEEE Computer Society
T2 - 16th IEEE International Conference on Control and Automation, ICCA 2020
Y2 - 9 October 2020 through 11 October 2020
ER -