The ELT M1 Local Coherencer is a non-contact metrology system aimed to simultaneously measure the relative pistons on the six sides of a target M1 segment with respect to neighbouring ones (reference segments) with an accuracy below 300nm in a range of ±250μm while it is supported by the M1 Segment Manipulator hanging from the M1 Segment Crane. For this purpose, the Local Coherencer is equipped with six Sensing Modules integrating a patented partially coherent light interferometer, an absolute tip-tilt sensor, a fine alignment system to orient the system normal to the reference segment and a coarse alignment detection system composed of a distance sensor and a border visualisation camera. The Preliminary Design described in a precedent paper has been further optimized to provide a better performance of the interferometer: a superluminiscent led (SLED) with a higher brilliance and spatial coherence has been selected to enhance the radiometry and contrast, the optical layout has been optimized to improve both the radiometric and wavefront degradation performance, additionally a detector with a bigger sensor area has been integrated to avoid the need of an afocal system to fit the output beam, thus further reducing the number of elements inducing beam degradation. As a part of the Final Design effort, an Early Unit of a Sensing Module has been built and tested to validate the expected performance, check the correct operation of the three measurement systems contained in the system as well as the local alignment system and tests the latency of the measurements. This paper describes the Final Design and the first results obtained with the aforementioned Early Unit of the Sensing Module.
In recent times, there has been a surge of interest in LiDAR imaging systems, particularly in outdoor terrestrial applications associated with computer vision. However, a significant hurdle preventing their widespread implementation lies in their limited tolerance for adverse weather conditions, such as fog. To address this challenge, researchers have explored the capability of polarization in improving detection capabilities in such media. This paper explores the potential of LiDAR technology to obtain polarized images through fog and investigates the impact of fog on object detection using digitized temporal signals and point clouds. The study utilizes a LiDAR-polarized imaging system using circular polarization, which has been shown to enhance image contrast in highly-dispersive media. The analysis of the polarimetric information of the backscattered light signal in fog reveals its influence on object detection and evaluates the range difference between orthogonal polarimetric channels: coplanar and cross-configuration. The results demonstrate that cross-configuration detection provides larger range and more detailed point clouds compared to co-planar configuration, particularly benefiting metallic objects, for the same foggy conditions. By utilizing circularly polarized incident light and cross-configuration detection, the LiDAR system can improve the signal-to-noise ratio by filtering out the co-polarized fog responses. However, the range of the system may be reduced compared to non-polarized detection. Overall, our findings indicate that utilizing a cross-polarization detection setup can effectively reduce the impact of fog backscatter while preserving the return signal from objects of interest in the majority of cases.
Automated systems increase their requirements in all fields, tightening their performance requirements in aspects like reliability, and ease of manipulation. Within this communication, we will present the development of a compact perception unit which includes a 3D lidar, RGB and thermal imaging for advanced perception purposes. The proposed unit intends to solve the usual hardware problems that software developers intend to solve in field applications. The basic features and performance of the system will be presented, and the applicability of the multimodal sensing approach presented to different applications in security, autonomous vehicles, and other application areas will be overviewed with examples.
KEYWORDS: Point clouds, LIDAR, Backscatter, Visibility through fog, Imaging systems, Signal processing, Signal detection, Object detection, 3D-TOF imaging
The interest in LiDAR imaging systems has recently increased in outdoor ground-based applications related to computer vision, in fields like autonomous vehicles. However, for the complete settling of the technology, there are still obstacles related to outdoor performance, being its use in adverse weather conditions one of the most challenging. When working in bad weather, data shown in point clouds is unreliable and its temporal behavior is unknown. We have designed, constructed, and tested a scanning-pulsed LiDAR imaging system with outstanding characteristics related to optoelectronic modifications, in particular including digitization capabilities of each of the pulses. The system performance was tested in a macro-scale fog chamber and, using the collected data, two relevant phenomena were identified: the backscattering signal of light that first interacts with the media and false-positive points that appear due to the scattering properties of the media. Digitization of the complete signal can be used to develop algorithms to identify and get rid of them. Our contribution is related to the digitization, analysis, and characterization of the acquired signal when steering to a target under foggy conditions, as well as the proposal of different strategies to improve point clouds generated in these conditions.
The ELT M1 Local Coherencer is a non-contact metrology system aimed to simultaneously measure the relative pistons on the six sides of a target M1 segment with respect to neighboring ones (reference segments) with an accuracy below 300nm in a range of ±250μm. This measurement shall be performed while the Local Coherencer is supported by the M1 Segment Manipulator hanging from the M1 Segment Crane. IDOM has developed for the M1 Local Coherencer a lean, compact and robust solution featuring: - Six lightweight and compact Sensing Modules whose main system is a partially coherent light interferometer for the piston measurements that hugely simplifies image processing and avoids any ambiguity in the measurements. - Comprehensive and robust alignment detection and alignment compensation systems that ensure proper positioning and prevent apparent (bias) piston measurement errors. - A lean embodiment in which all the subsystems, including control and safety elements, are mounted on a single support structure and enclosed in the specified design volume, with no need to use the space reserved in the M1 Segment Manipulator - A solution largely based on small COTS and simple electronics, which account for ease of use, high reliability, easy replaceability and high durability of the system. This paper describes the proposed design as presented in the Preliminary Design Review (PDR) of the system held in May 2022.
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