Name
Abstract | ||
|---|---|---|
Multiple lidars are used on mobile vehicles for rendering a broad view to enhance the performance of perception systems. However, precise calibration of multiple lidars is challenging since the feature correspondences in scan points arc sparse for providing enough constraints. To address this problem, existing methods require fixed calibration targets in scenes or rely exclusively on additional sensors. In this paper, we present a novel method that enables automatic lidar calibration without these restrictions. Three linearly independent planar surfaces appearing in surroundings is utilized to find correspondences. Two components are developed to ensure the extrinsic parameters to he found: a closed-form solver for initialization and an optimizer for refinement by minimizing a nonlinear cost function. Simulation and experimental results demonstrate the accuracy of our calibration approach with the rotation and translation errors smaller than 0.05rad and 0.1m respectively. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IVS.2019.8814136 | 2019 30TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV19) |
Field | DocType | ISSN |
Computer vision,Linear independence,Nonlinear system,Pattern recognition,Computer science,Planar,Lidar,Artificial intelligence,Solver,Initialization,Rendering (computer graphics),Calibration | Journal | 1931-0587 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianhao Jiao | 1 | 19 | 6.68 |
| Qinghai Liao | 2 | 8 | 2.24 |
| Yilong Zhu | 3 | 6 | 6.16 |
| Tianyu Liu | 4 | 1 | 0.34 |
| Yang Yu | 5 | 1 | 0.34 |
| Rui Fan | 6 | 258 | 28.91 |
| Lujia Wang | 7 | 80 | 14.13 |
| Ming Liu | 8 | 775 | 94.83 |