Nowadays, LiDARs hold a relevant place in providing the environmental sensing required by most ADAS. Promoted by such increasing demand, many new manufacturers are emerging and, new LiDARs are continuously made available on the market. If, on the one hand, the availability of LiDARs with increasing performance and reducing cost has brought significant benefits also promoting the spread of such measuring systems in other areas such as industrial controls and agriculture, on the other, it has made it more difficult to extricate in the immense set of LiDARs present on the market today. In response to this growing need for standards and methods capable of comparing the various LiDARs, many international standards and scientific publications are being produced on the subject. In this paper, we continue our work on LiDARs characterization, focusing our attention on comparing the performances of two of the most popular systems -namely, the MRS 1000 by Sick and the VLP 16 by Velodyne. Starting from the analysis of the warm-up time and stability, such a comparison focused on analyzing the axial error of both systems. Such errors have been estimated by exploiting a custom rail system and an absolute interferometer. The obtained results revealed warm-up times of a few tens of minutes and maximum absolute axial errors of a few centimeters in the range [1.5, 21] m.

LiDARs are considered essential for the environmental sensing required by most ADAS, including autonomous driving. Such has led to significant investments resulted in the availability of countless measuring systems that are increasingly performing and less expensive. Nevertheless, the extremely high speed of light still leads to a non-negligible quantization error in the direct time-of-flight (ToF) measure at the base of pulsed LiDARs -the leading technology for automotive applications. Hence, pulsed 3D-LiDARs analyze the surrounding by approximating and deforming it on concentric spheres whose radii are quantized with a quantization step that, for most commercial systems, is on the order of some centimeters. The deformation and error introduced by such quantization can thus be significant. In this study, we point out the approximations and assumptions intrinsic to 3D-LiDARs and propose a measurement procedure that, through the analysis of the fine variations of the target position, allows an accurate investigation of the axial resolution and error -probably among the few limitations still affecting this technology. To the best of our knowledge, this is the first study focused on the detailed analysis of the quantization error in 3D-LiDARs. The proposed method has been tested on one of the most popular 3D-LiDARs -namely the MRS 6000 by Sick. The obtained results revealed for the MRS 6000 a quantization step of about 6 cm (ToF quantization of about 0.4 ns) and an axial error normally distributed with experimental standard deviation of about 30 mm.

The vast multitude of LiDAR systems currently available on the market makes the need for methods to compare their performances increasingly high. In this study, we focus our attention on the development of a method for the analysis of the effects induced by the fog, one of the main challenges for Advanced Driver Assist Systems (ADASs) and autonomous driving. Large experimental setups capable of reconstructing adverse weather conditions on a large scale in a controlled and repeatable way are certainly the best test conditions to analyze and compare LiDARs performances in the fog. Nonetheless, such large plants are extremely expensive and complex, therefore only available in a few sites in the world. In this study, we thus propose a measurement method, a data analysis procedure and, an experimental setup that are extremely simple and inexpensive to implement. The achievable results are reasonably less accurate than those obtainable with large plants. Nevertheless, the proposed method can allow to easily and quickly obtain a preliminary estimate of the performance in the presence of fog and a rapid benchmarking of different LiDAR systems.

The development and testing of innovative technologies and automated data analysis methodologies offer tools for investigations in numerous scenarios including the monitoring of complex marine ecosystems and the direct and indirect effects of climate change on natural heritage. In the underwater environment, the creation of products with accurate metric and colorimetric content is a scientific and technological challenge, that can offer tools for new investigations including the monitoring of ecosystems and the study of biodiversity. The research group developed a technological solution consisting of a remotely operating platform and a measuring system that includes RGB and fluorescence optical sensors for the 3D reconstruction of the underwater environment and the study of the health-state of investigated species. The proposed solution aspires to high-accuracy multiscale reconstruction of underwater animal forests with a special focus on metric content. Methodologies and technical solutions for the management and calibration of the system have been developed: the design of proper calibration frames and the fluorescence sensor, the choice of a proper illumination system, the implementation of the system on a customizable Remotely Operating Vehicle, the integration of the different sensors, the combination of metric and colorimetric results for monitoring the occurred deformations and the health status. The results of laboratory activities and preliminary tests on field tests are discussed.