ICRA 2022poster11 citations

Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors

Sandipan Das, Navid Mahabadi, Addi Djikic, Cesar Nassir, Saikat Chatterjee, Maurice Fallon

Abstract

We demonstrate a multi-lidar calibration frame-work for large mobile platforms that jointly calibrate the extrinsic parameters of non-overlapping Field-of-View (FoV) lidar sensors, without the need for any external calibration aid. The method starts by estimating the pose of each lidar in its corresponding sensor frame in between subsequent timestamps. Since the pose estimates from the lidars are not necessarily synchronous, we first align the poses using a Dual Quaternion (DQ) based Screw Linear Interpolation. Afterward, a Hand-Eye based calibration problem is solved using the DQ-based formulation to recover the extrinsics. Furthermore, we verify the extrinsics by matching chosen lidar semantic features, obtained by projecting the lidar data into the camera perspective after time alignment using vehicle kinematics. Experimental results on the data collected from a Scania vehicle [~ 1 Km sequence] demonstrate the ability of our approach to obtain better calibration parameters than the provided vehicle CAD model calibration parameters. This setup can also be scaled to any combination of multiple lidars.

BibTeX
@inproceedings{icra2022_extrinsiccalibra,
  title = {Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors},
  author = {Sandipan Das and Navid Mahabadi and Addi Djikic and Cesar Nassir and Saikat Chatterjee and Maurice Fallon},
  booktitle = {ICRA 2022},
  year = {2022}
}
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors · ICRA 2022