IEEE Transactions on Instrumentation and Measurement · 2020 · 23 citations · 26 references
EngineeringAutomotive EngineeringSystems EngineeringMachine VisionRemote SensingSensorsCalibrationInterferometryOptical InstrumentationOptical MetrologyRange EstimationAdvanced Driver Assistance SystemsDriver Assistance System TestingDriver Assistance SystemsIndustrial Automation SystemsLidar InstrumentationLidar SensingLidar SensorsLidar Systems
LiDARs are becoming one of the pillars for the environmental sensing required by advanced driver assistance system (ADAS). Driven by the automotive industry, many new manufacturers are continuously putting new LiDARs on the market, thus increasing their availability and, concomitantly, reducing prices. Accordingly, LiDARs are today finding many new applications also in other fields, such as agriculture and industrial automation. In this article, we describe and discuss a measurement procedure for the analysis and comparison of the performances of LiDARs and report an example of the results obtained from the characterization of one the most widespread LiDARs—the VLP 16 by Velodyne. The proposed measurement procedure and setup have been designed to allow quick and easy installation and analysis of most LiDARs. In particular, they have been designed to allow the straightforward investigation of performances such as the warm-up, stability, and errors in the measured coordinates and parameters such as the spots pattern, waist, and divergence of the laser beams, thus allowing to analyze probably the most relevant performances and parameters for scanning LiDARs. Errors in the measured coordinates have been estimated using an absolute interferometer, whereas the beam parameters have been analyzed using a camera system. As an example, the analysis of the performances of the VLP 16 revealed a warm-up time of about 42 min and errors of few millimeters over a measuring interval of about (2, 21) m. On the other hand, the analysis of the laser beams revealed the vertical and horizontal beam divergences of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 1.2$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 3.9$ </tex-math></inline-formula> mrad, respectively.
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Faraz M. Mirzaei, Dimitrios G. Kottas, Stergios I. Roumeliotis · The International Journal of Robotics Research · 2012 · 161 citations
Performance Analysis of 10 Models of 3D LiDARs for Automated Driving
Jacob Lambert, Alexander Carballo, Abraham Monrroy et al. · IEEE Access · 2020 · 109 citations · Full text