TY - GEN
T1 - Lidar-only 3D SLAM System Comparative Study
AU - Ren, Wenhu
AU - Li, Xueyuan
AU - Li, Mengkai
AU - Liu, Qi
AU - Li, Zirui
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Simultaneous localization and mapping (SLAM) is an attractive and hot research topic in computer vision, robotics, and artificial intelligence. Autonomous vehicles driving in unknown environments try to perceive and map the surrounding environment while recognizing their location and trajectory. In this paper, five state-of-the-art open-source 3D lidar-only SLAM algorithms are reviewed: LOAM, LeGO-LOAM, F-LOAM, BALM, and MULLS. We briefly introduce the characteristics of these algorithms. Finally, the experimental comparison is carried out to compare the absolute pose error (APE), efficiency, and operation memory occupation of each algorithm.
AB - Simultaneous localization and mapping (SLAM) is an attractive and hot research topic in computer vision, robotics, and artificial intelligence. Autonomous vehicles driving in unknown environments try to perceive and map the surrounding environment while recognizing their location and trajectory. In this paper, five state-of-the-art open-source 3D lidar-only SLAM algorithms are reviewed: LOAM, LeGO-LOAM, F-LOAM, BALM, and MULLS. We briefly introduce the characteristics of these algorithms. Finally, the experimental comparison is carried out to compare the absolute pose error (APE), efficiency, and operation memory occupation of each algorithm.
UR - http://www.scopus.com/inward/record.url?scp=85146800308&partnerID=8YFLogxK
U2 - 10.1109/ICARCV57592.2022.10004296
DO - 10.1109/ICARCV57592.2022.10004296
M3 - Conference contribution
AN - SCOPUS:85146800308
T3 - 2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022
SP - 505
EP - 510
BT - 2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022
Y2 - 11 December 2022 through 13 December 2022
ER -