Automated Rotational Calibration of Multiple 3D LIDAR Units for Intelligent Vehicles

被引:0
作者
Maroli, John M. [1 ]
Ozguner, Umit [1 ]
Redmill, Keith [1 ]
Kurt, Arda [1 ]
机构
[1] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43210 USA
来源
2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | 2017年
关键词
calibration; intelligent transportation; ground plane identification; genetic algorithm; occupancy grid map;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new calibration method is introduced for automatically and simultaneously determining roll, pitch, and yaw offsets of multiple 3D Light Detection and Ranging (LIDAR) sensors from their theoretical values. The application focuses on autonomous ground vehicles with a LIDAR unit on each of four sides, but can be extended to other multi-LIDAR configurations as well. The data from the LIDAR units is combined to form a 3D point cloud representing the vehicle's surroundings. There are two parts to the calibration: the ground plane alignment that determines and corrects the roll and pitch offsets of each LIDAR independently, and the genetic algorithm based alignment that determines and corrects the yaw offsets of all LIDARs simultaneously. In the ground plane alignment, a scan from each LIDAR is used to calculate the roll and pitch offset of the sensed ground plane from the theoretical ground plane. A correction is applied to the data and a genetic algorithm is then used to concurrently determine the yaw offsets.
引用
收藏
页数:6
相关论文
共 15 条
  • [1] [Anonymous], 2012, PROC 26 AAAI C ARTIF
  • [2] Merging occupancy grid maps from multiple robots
    Birk, Andreas
    Carpin, Stefano
    [J]. PROCEEDINGS OF THE IEEE, 2006, 94 (07) : 1384 - 1397
  • [3] Choi D.-G., 2016, IEEE T ROBOTICS, V32
  • [4] USING OCCUPANCY GRIDS FOR MOBILE ROBOT PERCEPTION AND NAVIGATION
    ELFES, A
    [J]. COMPUTER, 1989, 22 (06) : 46 - 57
  • [5] He M., 2014, IEEE INT C ROB AUT I
  • [6] Himmelsbach M., 2010, IEEE INT VEH S SAN D
  • [7] John V., 2015, IEEE INT C VEH EL SA
  • [8] Kang J., 2016, IEEE T ROBOTICS, V32
  • [9] Levinson J., 2014, Experimental Robotics, P179
  • [10] Multivehicle Cooperative Local Mapping: A Methodology Based on Occupancy Grid Map Merging
    Li, Hao
    Tsukada, Manabu
    Nashashibi, Fawzi
    Parent, Michel
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 15 (05) : 2089 - 2100