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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hang Dong Anderson, S. Barfoot, T.D. |
| Copyright Year | 2013 |
| Description | Author affiliation: Autonomous Space Robot. Lab., Univ. of Toronto, Toronto, ON, Canada (Hang Dong; Anderson, S.; Barfoot, T.D.) |
| Abstract | Accurate pose estimation relies on high-quality sensor measurements. Due to manufacturing tolerance, every sensor (camera or lidar) needs to be individually calibrated. Feature-based techniques using simple calibration targets (e.g., a checkerboard pattern) have become the dominant approach to camera sensor calibration. Existing lidar calibration methods require a controlled environment (e.g., a space of known dimension) or specific configurations of supporting hardware (e.g., coupled with GPS/IMU). Leveraging recent state estimation developments based on lidar intensity imagery, this paper presents a calibration procedure for a two-axis scanning lidar using only an inexpensive checkerboard calibration target. In addition, the proposed method generalizes a two-axis scanning lidar as an idealized spherical camera with additive measurement distortions. Conceptually, this is not unlike normal camera calibration in which an arbitrary camera is modelled as an idealized projective (pinhole) camera with tangential and radial distortions. The resulting calibration method, we believe, can be readily applied to a variety of two-axis scanning lidars. We present the measurement improvement quantitatively, as well as the impact of calibration on a 1.1-km visual odometry estimate. |
| Starting Page | 3672 |
| Ending Page | 3678 |
| File Size | 1724747 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781467356411 |
| ISSN | 10504729 |
| e-ISBN | 9781467356435 |
| DOI | 10.1109/ICRA.2013.6631093 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-06 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Calibration Laser radar Robot sensing systems Cameras Distortion measurement Mathematical model Mirrors |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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