TY - JOUR
T1 - Application of sparse-channel lidar sensors on viewpoint-invariant loop closing task
AU - Cao, Fengkui
AU - Wu, Hao
AU - Wu, Chengdong
PY - 2022/7/15
Y1 - 2022/7/15
N2 - Loop closing is an essential task for SLAM system, which can reduce the pose drifts and map distortion. However, challenges from viewpoint changes and sparse-channel lidar are still open problems. In this paper, a novel efficient and viewpoint-invariant loop closing method is presented, which well fits sparse-channel lidars. To keep the metric information of 3D point clouds, elevation maps are explored to represent sparse point clouds, based on which a novel and viewpoint-invariant key point feature detection method is proposed. To improve efficiency, Bag of Words technique is applied to accelerate the process of scene description and matching. In addition, a strict geometric consistency check of matched key point pairs is proposed to reject false positive detections, which makes our method robust to scenes with similar layouts in urban environments. Extensive experiments on challenging public datasets verify the validity and superiority of the proposed method.[Graphic presents]
AB - Loop closing is an essential task for SLAM system, which can reduce the pose drifts and map distortion. However, challenges from viewpoint changes and sparse-channel lidar are still open problems. In this paper, a novel efficient and viewpoint-invariant loop closing method is presented, which well fits sparse-channel lidars. To keep the metric information of 3D point clouds, elevation maps are explored to represent sparse point clouds, based on which a novel and viewpoint-invariant key point feature detection method is proposed. To improve efficiency, Bag of Words technique is applied to accelerate the process of scene description and matching. In addition, a strict geometric consistency check of matched key point pairs is proposed to reject false positive detections, which makes our method robust to scenes with similar layouts in urban environments. Extensive experiments on challenging public datasets verify the validity and superiority of the proposed method.[Graphic presents]
UR - http://www.scopus.com/inward/record.url?scp=85132691752&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2022.3178392
DO - 10.1109/JSEN.2022.3178392
M3 - Article
AN - SCOPUS:85132691752
SN - 1530-437X
VL - 22
SP - 14592
EP - 14600
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 14
ER -