Two-axis scanning lidar geometric calibration using intensity imagery and distortion mapping

Dong, Hang; Anderson, Sean; Barfoot, Timothy D.

doi:10.1109/icra.2013.6631093

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…12). This procedure is described by Dong et al [9], but briefly the calibration uses multiple images of checkerboards at known locations to solve for intrinsic parameters by calculating the poses of the checkerboards. We effectively calibrate the azimuth, elevation, and range images in the lidar image stack of Fig.…”

Section: Lidar Calibrationmentioning

confidence: 99%

Into Darkness: Visual Navigation Based on a Lidar-Intensity-Image Pipeline

Barfoot¹,

McManus²,

Anderson³

et al. 2023

Preprint

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Visual navigation of mobile robots has become a core capability that enables many interesting applications from planetary exploration to self-driving cars. While systems built on passive cameras have been shown to be robust in well-lit scenes, they cannot handle the range of conditions associated with a full diurnal cycle. Lidar, which is fairly invariant to ambient lighting conditions, offers one possible remedy to this problem. In this paper, we describe a visual navigation pipeline that exploits lidar’s ability to measure both range and intensity (a.k.a., reflectance) information. In particular, we use lidar intensity images (from a scanning-laser rangefinder) to carry out tasks such as visual odometry (VO) and visual teach and repeat (VT&R) in realtime, from full-light to full-dark conditions. This lighting invariance comes at the price of coping with motion distortion, owing to the scanning-while-moving nature of laser-based imagers. We present our results and lessons learned from the last few years of research in this area.

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Section: Lidar Calibrationmentioning

confidence: 99%

Into Darkness: Visual Navigation Based on a Lidar-Intensity-Image Pipeline

Barfoot¹,

McManus²,

Anderson³

et al. 2023

Preprint

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Calibration of a Rotating Laser Range Finder using Intensity Features

Katuwandeniya

Ranasinghe

Dantanarayana

et al. 2018

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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This paper presents an algorithm for calibrating a "3D range sensor" constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process.

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Calibration of Planar Reflectors Reshaping LiDAR’s Field of View

Pełka¹,

Bedkowski

2021

Sensors

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This paper describes the calibration method for calculating parameters (position and orientation) of planar reflectors reshaping LiDAR’s (light detection and ranging) field of view. The calibration method is based on the reflection equation used in the ICP (Iterative Closest Point) optimization. A novel calibration process as the multi-view data registration scheme is proposed; therefore, the poses of the measurement instrument and parameters of planar reflectors are calculated simultaneously. The final metric measurement is more accurate compared with parameters retrieved from the mechanical design. Therefore, it is evident that the calibration process is required for affordable solutions where the mechanical design can differ from the inaccurate assembly. It is shown that the accuracy is less than 20 cm for almost all measurements preserving long-range capabilities. The experiment is performed based on Livox Mid-40 LiDAR augmented with six planar reflectors. The ground-truth data were collected using Z + F IMAGER 5010 3D Terrestrial Laser Scanner. The calibration method is independent of mechanical design and does not require any fiducial markers on the mirrors. This work fulfils the gap between rotating and Solid-State LiDARs since the field of view can be reshaped by planar reflectors, and the proposed method can preserve the metric accuracy. Thus, such discussion concludes the findings. We prepared an open-source project and provided all the necessary data for reproducing the experiments. That includes: Complete open-source code, the mechanical design of reflector assembly and the dataset which was used in this paper.

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Two-axis scanning lidar geometric calibration using intensity imagery and distortion mapping

Cited by 5 publications

References 11 publications

Into Darkness: Visual Navigation Based on a Lidar-Intensity-Image Pipeline

Into Darkness: Visual Navigation Based on a Lidar-Intensity-Image Pipeline

Calibration of a Rotating Laser Range Finder using Intensity Features

Calibration of Planar Reflectors Reshaping LiDAR’s Field of View

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