In order to retrieve a highly accurate view of their environment, autonomous cars are often equipped with LiDAR sensors. These sensors deliver a three dimensional point cloud in their own co-ordinate frame, where the origin is the sensor itself. However, the common co-ordinate system required by HAD (Highly Autonomous Driving) software systems has its origin at the center of the vehicle’s rear axle. Thus, a transformation of the acquired point clouds to car co-ordinates is necessary, and thereby the determination of the exact mounting position of the LiDAR system in car coordinates is required. Unfortunately, directly measuring this position is a time-consuming and error-prone task. Therefore, different approaches have been suggested for its estimation which mostly require an exhaustive test-setup and are again time-consuming to prepare. When preparing a high number of LiDAR mounted test vehicles for data acquisition, most approaches fall short due to time or money constraints. In this paper we propose an approach for mounting position estimation which features an easy execution and setup, thus making it feasible for on-field calibration.
Owes Khan, René Bergelt, and Wolfram Hardt, "On-field mounting position estimation of a lidar sensor," Proc. SPIE 10431, Remote Sensing Technologies and Applications in Urban Environments II, 104310Q (Presented at SPIE Remote Sensing: September 12, 2017; Published: 4 October 2017); https://doi.org/10.1117/12.2278396.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the conference proceedings. They include the speaker's narration along with a video recording of the presentation slides and animations. Many conference presentations also include full-text papers. Search and browse our growing collection of more than 12,000 conference presentations, including many plenary and keynote presentations.