Abstract
This paper presents a novel calibration method for solid-state LiDAR devices based on a geometrical description of their scanning system, which has variable angular resolution. Determining this distortion across the entire Field-of-View of the system yields accurate and precise measurements which enable it to be combined with other sensors. On the one hand, the geometrical model is formulated using the well-known Snell’s law and the intrinsic optical assembly of the system, whereas on the other hand the proposed method describes the scanned scenario with an intuitive camera-like approach relating pixel locations with scanning directions. Simulations and experimental results show that the model fits with real devices and the calibration procedure accurately maps their variant resolution so undistorted representations of the observed scenario can be provided. Thus, the calibration method proposed during this work is applicable and valid for existing scanning systems improving their precision and accuracy in an order of magnitude.
Highlights
Nowadays, Light Detection and Ranging (LiDAR) devices are aimed to be used in a wide variety of applications among which autonomous vehicles and computer vision for robotics are outstanding
This paper presents a novel calibration method for solid-state LiDAR devices based on a geometrical description of their scanning system, which has variable angular resolution
We have introduced a geometrical model for the scanning system of a LiDAR device based only in Snell’s law and its specific mechanics, what allows using the same procedure for other scanning techniques, either solid-state based or mechanical ones, as long as its scanning principle is carefully described
Summary
Light Detection and Ranging (LiDAR) devices are aimed to be used in a wide variety of applications among which autonomous vehicles and computer vision for robotics are outstanding. Their first studies and uses were related to atmospheric observations [1,2,3] and airborne mapping [4,5] decades ago. The current disruption of autonomous driving and robotics has forced LiDAR technology to move a step forward in order to meet their demanding specifications: large range and high spatial resolution whilst real-time performance and background solar tolerance. They have been widely used in research and some industrial applications [10,11,12], solid-state LiDARs which precisely avoid large mechanical parts have arisen great interest because they provide scalability, reliability and embeddedness
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