Simple Camera-to-2D-LiDAR Calibration Method for General Use

Extrinsic Calibration of Rotating 2d Laser Range Finder and Camera Using Photogrammetric Test Field and Ping Pong Balls

“…The following features should be present in any extrinsic calibration method for calibrating a 2D LRF and a camera for non-experts: 1) The calibration target should be simple to build and detect, 2) The capability of the system to determine transformation values from a single sample, and 3) the system must be capable of coping with circumstances in which the camera and laser are not pointed in the same general direction (Palmer et al 2020) 4) In situations where extrinsic calibration is used, such as in autonomous cars, it should be possible to update or modify it. Previous techniques (Ahmad Yousef et al 2017) (Hillemann and Jutzi 2017) (Vasconcelos, Barreto, and Nunes 2012) (Gao et al 2003) depended on identifying lines in laser readings and checkerboard patterns in images.…”

“…Trihedron-based techniques for figuring out the height at which the laser meets the target have been created as a result (Gomez-Ojeda et al 2015) (Hu et al 2016). These targets, however, suffer from rotating problems, which is why techniques that made use of a v-shaped test field (Palmer et al 2020) were created. Additionally, it has the benefit of allowing calibration from a single sample.…”

“…Additionally, it has the benefit of allowing calibration from a single sample. Only (Palmer et al 2020) employed ping-pong balls in any of the earlier techniques to calibrate the laser and camera, which had vastly different perspectives of the target. However, their method was not compared with the trihedron-based methods and The advantage of employing photogrammetric bundle adjustment (Fraser 1997) (Cronk, Fraser, and Hanley 2006) (Abbas et al 2014) (Hosseininaveh et al 2014) for precisely predicting the center of the ping pong balls were neglected because they used just one image for calibration.…”

“…This paper suggests a method for calibrating a camera and a 2D LRF using a photogrammetric test field to address the shortcomings and restrictions of earlier methods. Trihedronbased approaches (Zhu et al 2020) (Fan et al 2019) and spherical target-based methods (Palmer et al 2020) can both use the test field. In addition to employing the room's corner and ping-pong balls, bundle adjustment was employed as a contribution of this study to the related work (Zhu et al 2020) (Palmer et al 2020) (Fan et al 2019) as an accurate approach for 3D measurements of targets (the center of the ping-pong balls) and the posture of the camera.…”

“…Trihedronbased approaches (Zhu et al 2020) (Fan et al 2019) and spherical target-based methods (Palmer et al 2020) can both use the test field. In addition to employing the room's corner and ping-pong balls, bundle adjustment was employed as a contribution of this study to the related work (Zhu et al 2020) (Palmer et al 2020) (Fan et al 2019) as an accurate approach for 3D measurements of targets (the center of the ping-pong balls) and the posture of the camera. Additionally, this work compares spherical target-based approaches with trihedronbased methods, which have not before been done in the literature.…”