Velocity Estimation from LiDAR Sensors Motion Distortion Effect.

Many modern automated vehicle sensor systems use light detection and ranging (LiDAR) sensors. The prevailing technology is scanning LiDAR, where a collimated laser beam illuminates objects sequentially point-by-point to capture 3D range data. In current systems, the point clouds from the LiDAR sensors are mainly used for object detection. To estimate the velocity of an object of interest (OoI) in the point cloud, the tracking of the object or sensor data fusion is needed. Scanning LiDAR sensors show the motion distortion effect, which occurs when objects have a relative velocity to the sensor. Often, this effect is filtered, by using sensor data fusion, to use an undistorted point cloud for object detection. In this study, we developed a method using an artificial neural network to estimate an object's velocity and direction of motion in the sensor's field of view (FoV) based on the motion distortion effect without any sensor data fusion. This network was trained and evaluated with a synthetic dataset featuring the motion distortion effect. With the method presented in this paper, one can estimate the velocity and direction of an OoI that moves independently from the sensor from a single point cloud using only one single sensor. The method achieves a root mean squared error (RMSE) of 0.1187 m s-1 and a two-sigma confidence interval of [-0.0008 m s-1, 0.0017 m s-1] for the axis-wise estimation of an object's relative velocity, and an RMSE of 0.0815 m s-1 and a two-sigma confidence interval of [0.0138 m s-1, 0.0170 m s-1] for the estimation of the resultant velocity. The extracted velocity information (4D-LiDAR) is available for motion prediction and object tracking and can lead to more reliable velocity data due to more redundancy for sensor data fusion.

A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors.

In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain.

Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard.

Measurement performance evaluation of real and virtual automotive light detection and ranging (LiDAR) sensors is an active area of research. However, no commonly accepted automotive standards, metrics, or criteria exist to evaluate their measurement performance. ASTM International released the ASTM E3125-17 standard for the operational performance evaluation of 3D imaging systems commonly referred to as terrestrial laser scanners (TLS). This standard defines the specifications and static test procedures to evaluate the 3D imaging and point-to-point distance measurement performance of TLS. In this work, we have assessed the 3D imaging and point-to-point distance estimation performance of a commercial micro-electro-mechanical system (MEMS)-based automotive LiDAR sensor and its simulation model according to the test procedures defined in this standard. The static tests were performed in a laboratory environment. In addition, a subset of static tests was also performed at the proving ground in natural environmental conditions to determine the 3D imaging and point-to-point distance measurement performance of the real LiDAR sensor. In addition, real scenarios and environmental conditions were replicated in the virtual environment of a commercial software to verify the LiDAR model's working performance. The evaluation results show that the LiDAR sensor and its simulation model under analysis pass all the tests specified in the ASTM E3125-17 standard. This standard helps to understand whether sensor measurement errors are due to internal or external influences. We have also shown that the 3D imaging and point-to-point distance estimation performance of LiDAR sensors significantly impacts the working performance of the object recognition algorithm. That is why this standard can be beneficial in validating automotive real and virtual LiDAR sensors, at least in the early stage of development. Furthermore, the simulation and real measurements show good agreement on the point cloud and object recognition levels.

Co-linear common-path shearography with a zero-approaching shear amount and separate control of the spatial carrier for single-shot phase measurement.

A co-linear common-path shearography is proposed with spatial phase shift for single-shot phase measurement. The co-linear common-path configuration brings an enhanced robustness and stability of the measuring system, because the two laterally sheared interfering object waves propagate essentially along the same path, which cancels out the disturbance and noise in surroundings. Two functional features, which break through the limitations in conventional co-linear common-path shearography, are proposed and implemented, namely the zero-approaching shear amount and the separate control of the spatial carrier. Seldom shearography configured by co-linear common-path structure possesses with these two features, because the linearly aligned optics restricts the control parameters in regards to the shear amount and the spatial carrier. In the proposed scheme, an intermediate real image plane is created in the linearly aligned light path to address the issue of zero-approaching shear amount. A 4-f imaging system is embedded with an aperture in between to implement a separate control of the spatial carrier. The zero-approaching shear amount provides the sufficiently small shear to make sure the strain or slope field of complex deformation is resolvable. Meanwhile, the separate control of the spatial carrier further guarantees a well-distributed spatial frequency spectrum when the required zero-approaching shear amount is configured.

Low-cost scanning LIDAR architecture with a scalable frame rate for autonomous vehicles.

Autonomous vehicles need accurate 3D perception with a decent frame rate and high angular resolution to detect obstacles reliably and avoid collisions. We developed a low-cost scanning multichannel light detection and ranging sensor architecture allowing scalable frame rates by adjusting the number of laser and detector pairs. Scanning is achieved by a pair of micro-electro-mechanical system (MEMS) mirrors. A control pattern for the MEMS mirrors to maximize the frame rate is presented. A built prototype based on the proposed architecture achieves a frame rate of 11.5 Hz, a field of view of 70∘×30∘, and an angular resolution of 0.4°. The distance resolution is 6 cm. Reliable single-shot detection for low-reflective objects up to 19 m indoors and 11 m under direct sunlight exposure is achieved. A performance assessment based on the presented measurement system for recently available vertical-cavity surface-emitting laser arrays with power densities up to 1k W/m m 2 shows promising improvement potential.

Temperature-decoupled hydrogen sensing with Pi-shifted fiber Bragg gratings and a partial palladium coating.

A novel, to the best of our knowledge, sensor architecture for palladium-coated fiber Bragg gratings is proposed and demonstrated that allows highly accurate multi-parameter sensing and decoupling of hydrogen concentration from temperature. By means of partly Pd-coated Pi-shifted FBGs (PSFBGs), the notch wavelength of the narrow transmission band and the flank wavelength of the broader reflection band experience different hydrogen and temperature sensitivities. PSFBGs were calibrated at hydrogen concentrations between 800 and 10,000 ppm and temperatures from 20 to 40°C, and a decreased hydrogen sensitivity at increased temperatures was found. Nonlinear temperature-dependent hydrogen calibration functions were therefore determined. An iterative matrix algorithm was used to decouple hydrogen concentration and temperature and to account for the nonlinear calibration functions. Achieved improvements and results have great importance for real field applications of FBG-based hydrogen sensing.

Generalized and wavelength-dependent temperature calibration function for multipoint regenerated fiber Bragg grating sensors.

A new calibration methodology for regenerated fiber Bragg grating (RFBG) temperature sensors up to 700 °C is proposed and demonstrated. A generalized, wavelength-dependent temperature calibration function is experimentally determined that describes the temperature-induced wavelength shifts for all RFBG sensor elements that are manufactured with the same fabrication parameters in the wavelength range from 1465 nm to 1605 nm. Using this generalized calibration function for absolute temperature measurements, each RFBG sensor element only needs to be calibrated at one reference temperature, representing a considerable simplification of the conventional calibration procedure. The new calibration methodology was validated with 7 RFBGs, and uncertainties were found to be compliant with those of Class 1 thermocouples (< ±1.5 K or < ±0.4% of the measured temperature). The proposed calibration technique overcomes difficulties with the calibration of spatially extended multipoint RFBG sensor arrays, where setting up an adequate calibration facility for large sensor fibers is challenging and costly. We assume that this calibration method can also be adapted to other types of FBG temperature sensors besides RFBGs. An accurate and practical calibration approach is essential for the acceptance and dissemination of the fiber-optic multipoint temperature sensing technology.

Development of High-Fidelity Automotive LiDAR Sensor Model with Standardized Interfaces.

This work introduces a process to develop a tool-independent, high-fidelity, ray tracing-based light detection and ranging (LiDAR) model. This virtual LiDAR sensor includes accurate modeling of the scan pattern and a complete signal processing toolchain of a LiDAR sensor. It is developed as a functional mock-up unit (FMU) by using the standardized open simulation interface (OSI) 3.0.2, and functional mock-up interface (FMI) 2.0. Subsequently, it was integrated into two commercial software virtual environment frameworks to demonstrate its exchangeability. Furthermore, the accuracy of the LiDAR sensor model is validated by comparing the simulation and real measurement data on the time domain and on the point cloud level. The validation results show that the mean absolute percentage error (MAPE) of simulated and measured time domain signal amplitude is 1.7%. In addition, the MAPE of the number of points Npoints and mean intensity Imean values received from the virtual and real targets are 8.5% and 9.3%, respectively. To the author's knowledge, these are the smallest errors reported for the number of received points Npoints and mean intensity Imean values up until now. Moreover, the distance error derror is below the range accuracy of the actual LiDAR sensor, which is 2 cm for this use case. In addition, the proving ground measurement results are compared with the state-of-the-art LiDAR model provided by commercial software and the proposed LiDAR model to measure the presented model fidelity. The results show that the complete signal processing steps and imperfections of real LiDAR sensors need to be considered in the virtual LiDAR to obtain simulation results close to the actual sensor. Such considerable imperfections are optical losses, inherent detector effects, effects generated by the electrical amplification, and noise produced by the sunlight.

Temperature and external strain sensing with metal-embedded optical fiber sensors for structural health monitoring.

An optical fiber with both temperature and strain fiber Bragg grating sensors were embedded into an aluminum cast structure during the casting process. Temperature and strain calibrations were carried out respectively for the metal-embedded sensors. Temperature and external strain decoupling was further demonstrated in a temperature range from 25 to 80 °C and an external strain range from 0 to ∼110 µÉ›. With the interpolated temperature measured by two temperature sensors at different positions, the external strain could be decoupled from temperature and thermal strain at the strain sensor. The temperature and external strain values obtained from our embedded optical fiber sensors agreed well with reference values, revealing the good performance of the metal-embedded optical fiber sensors. The difference between the measured values and the reference values are within ±5 µÉ› for external strain and ±1 °C for temperature. With only a single fiber, the in-situ temperature and external strain information in the aluminum structure can be monitored in real time, representing an important step towards fiber-optic smart casts. Our investigation demonstrates that embedded optical fiber sensors can be a promising method for structural health monitoring of metallic structures.

Super-compact shearography based on a single diffractive optical element with 3-in-1 phase mask.

This Letter communicates a new, to the best of our knowledge, designing framework of shearography. The three elementary functional parts of quantitative shearography, namely imaging, shearing, and phase shifting, are integrated into a single diffractive optical element (DOE), named a 3-in-1 phase mask. The idea breaks through the conventional designing routine of shearography, and converts it from the combination of individual optical elements to the spatial manipulation of phase. The slicing, splicing, and alternating strategy is proposed to generate the 3-in-1 phase mask from a given number of sequenced Fresnel lenses and a modified echelle grating. The operating component is merely a DOE, which renders the optics naturally coaxial. The delivered shearography system enjoys a super-compact configuration, a high level of robustness and stability, and the potential for implementing outside optics laboratories. Crucial system parameters, e.g., shear amount, shear direction, working distance, can be readily shifted on call by re-making the 3-in-1 phase mask. The future of the present idea is in its shape and seems promising with lithography, micromachining, and metasurfaces.

Identification of a PCSK9-LDLR disruptor peptide with in vivo function.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) regulates plasma low-density lipoprotein cholesterol (LDL-C) levels by promoting hepatic LDL receptor (LDLR) degradation. Therapeutic antibodies that disrupt PCSK9-LDLR binding reduce LDL-C concentrations and cardiovascular disease risk. The epidermal growth factor precursor homology domain A (EGF-A) of the LDLR serves as a primary contact with PCSK9 via a flat interface, presenting a challenge for identifying small molecule PCSK9-LDLR disruptors. We employ an affinity-based screen of 1013in vitro-translated macrocyclic peptides to identify high-affinity PCSK9 ligands that utilize a unique, induced-fit pocket and partially disrupt the PCSK9-LDLR interaction. Structure-based design led to molecules with enhanced function and pharmacokinetic properties (e.g., 13PCSK9i). In mice, 13PCSK9i reduces plasma cholesterol levels and increases hepatic LDLR density in a dose-dependent manner. 13PCSK9i functions by a unique, allosteric mechanism and is the smallest molecule identified to date with in vivo PCSK9-LDLR disruptor function.

Optical Fiber Sensor for Temperature and Strain Measurement Based on Multimode Interference and Square-Core Fiber.

A variety of specialty fibers such as no-core fiber (NCF) have already been studied to reveal their sensing abilities. In this work, we investigate a specialty fiber, square-core fiber, for temperature and strain sensing. A simple single-mode-multimode-single-mode (SMS) fiber sensor was fabricated, consisting of a 30-cm-long square-core fiber. The experimental results indicate that the maximal wavelength-temperature and wavelength-strain sensitivities are -15.3 pm/∘C and -1.5 pm/µÎµ, respectively, while the maximal power-temperature and power-strain sensitivities are 0.0896 dBm/∘C and 0.0756 dBm/µÎµ. Analysis of the results suggests that the fiber sensor has the potential to be used as a high-sensitivity temperature sensor with a low strain sensitivity.

Smartphone-based colorimetric detection system for portable health tracking.

Colorimetric tests for at-home health monitoring became popular 50 years ago with the advent of the urinalysis test strips, due to their reduced costs, practicality, and ease of operation. However, developing digital systems that can interface these sensors in an efficient manner remains a challenge. Efforts have been put towards the development of portable optical readout systems, such as smartphones. However, their use in daily settings is still limited by their error-prone nature associated to optical noise from the ambient lighting, and their low sensitivity. Here, a smartphone application (Colourine) to readout colorimetric signals was developed on Android OS and tested on commercial urinalysis test strips for pH, proteins, and glucose detection. The novelty of this approach includes two features: a pre-calibration step where the user is asked to take a photo of the commercial reference chart, and a CIE-RGB-to-HSV color space transformation of the acquired data. These two elements allow the background noise given by environmental lighting to be minimized. The sensors were characterized in the ambient light range 100-400 lx, yielding a reliable output. Readouts were taken from urine strips in buffer solutions of pH (5.0-9.0 units), proteins (0-500 mg dL-1) and glucose (0-1000 mg dL-1), yielding a limit of detection (LOD) of 0.13 units (pH), 7.5 mg dL-1 (proteins) and 22 mg dL-1 (glucose), resulting in an average LOD decrease by about 2.8 fold compared to the visual method.

Extension and Limits of Depolarization-Fringe Contrast Roughness Method in Sub-Micron Domain.

To guarantee quality standards for the industry, surface properties, particularly those of roughness, must be considered in many areas of application. Today, several methods are available on the market, but some damage the surface to be tested as they measure it by contact. A non-contact method for the precise estimation of sub-micron roughness values is presented, which can be used as an extension of existing roughness measurement techniques to improve them further considering the depolarized light reflected by the sample. This setup is based on a Michelson interferometer, and by introducing a quarter-wave plate on a half part of the reference mirror, the surface roughness can be directly derived by measuring the fringe contrasts. This article introduces a simple model describing the intensity distortions resulting from the microscopic roughness in divided interferograms when considering depolarization. This work aimed to extend the measurement range of the technique developed in a previous work, in which depolarization effects are taken into account. For verification, the experimental results were compared with the fringe contrast technique, which does not consider the depolarization of the scattered light, especially regarding the extended wavelength interval, highlighting the limits of the technique. In addition, simulations of the experiments are presented. For comparison, the reference values of the sample roughness were also generated by measurements with a stylus profiler.

Fiber Bragg Sensors Embedded in Cast Aluminum Parts: Axial Strain and Temperature Response.

In this study, the response of fiber Bragg gratings (FBGs) embedded in cast aluminum parts under thermal and mechanical load were investigated. Several types of FBGs in different types of fibers were used in order to verify general applicability. To monitor a temperature-induced strain, an embedded regenerated FBG (RFBG) in a cast part was placed in a climatic chamber and heated up to 120 ∘C within several cycles. The results show good agreement with a theoretical model, which consists of a shrink-fit model and temperature-dependent material parameters. Several cast parts with different types of FBGs were machined into tensile test specimens and tensile tests were executed. For the tensile tests, a cyclic procedure was chosen, which allowed us to distinguish between the elastic and plastic deformation of the specimen. An analytical model, which described the elastic part of the tensile test, was introduced and showed good agreement with the measurements. Embedded FBGs - integrated during the casting process - showed under all mechanical and thermal load conditions no hysteresis, a reproducible sensor response, and a high reliable operation, which is very important to create metallic smart structures and packaged fiber optic sensors for harsh environments.

3D Deep Learning Enables Accurate Layer Mapping of 2D Materials.

Layered, two-dimensional (2D) materials are promising for next-generation photonics devices. Typically, the thickness of mechanically cleaved flakes and chemical vapor deposited thin films is distributed randomly over a large area, where accurate identification of atomic layer numbers is time-consuming. Hyperspectral imaging microscopy yields spectral information that can be used to distinguish the spectral differences of varying thickness specimens. However, its spatial resolution is relatively low due to the spectral imaging nature. In this work, we present a 3D deep learning solution called DALM (deep-learning-enabled atomic layer mapping) to merge hyperspectral reflection images (high spectral resolution) and RGB images (high spatial resolution) for the identification and segmentation of MoS2 flakes with mono-, bi-, tri-, and multilayer thicknesses. DALM is trained on a small set of labeled images, automatically predicts layer distributions and segments individual layers with high accuracy, and shows robustness to illumination and contrast variations. Further, we show its advantageous performance over the state-of-the-art model that is solely based on RGB microscope images. This AI-supported technique with high speed, spatial resolution, and accuracy allows for reliable computer-aided identification of atomically thin materials.

MEMS-Scanner Testbench for High Field of View LiDAR Applications.

LiDAR sensors are a key technology for enabling safe autonomous cars. For highway applications, such systems must have a long range, and the covered field of view (FoV) of >45° must be scanned with resolutions higher than 0.1°. These specifications can be met by modern MEMS scanners, which are chosen for their robustness and scalability. For the automotive market, these sensors, and especially the scanners within, must be tested to the highest standards. We propose a novel measurement setup for characterizing and validating these kinds of scanners based on a position-sensitive detector (PSD) by imaging a deflected laser beam from a diffuser screen onto the PSD. A so-called ray trace shifting technique (RTST) was used to minimize manual calibration effort, to reduce external mounting errors, and to enable dynamical one-shot measurements of the scanner's steering angle over large FoVs. This paper describes the overall setup and the calibration method according to a standard camera calibration. We further show the setup's capabilities by validating it with a statically set rotating stage and a dynamically oscillating MEMS scanner. The setup was found to be capable of measuring LiDAR MEMS scanners with a maximum FoV of 47° dynamically, with an uncertainty of less than 1%.

Optical Setup for Error Compensation in a Laser Triangulation System.

Absolute distance measurement is a field of research with a large variety of applications. Laser triangulation is a well-tested and developed technique using geometric relations to calculate the absolute distance to an object. The advantages of laser triangulation include its simple and cost-effective setup with yet a high achievable accuracy and resolution in short distances. A main problem of the technology is that even small changes of the optomechanical setup, e.g., due to thermal expansion, lead to significant measurement errors. Therefore, in this work, we introduce an optical setup containing only a beam splitter and a mirror, which splits the laser into a measurement beam and a reference beam. The reference beam can then be used to compensate for different error sources, such as laser beam dithering or shifts of the measurement setup due to the thermal expansion of the components. The effectiveness of this setup is proven by extensive simulations and measurements. The compensation setup improves the deviation in static measurements by up to 75%, whereas the measurement uncertainty at a distance of 1 m can be reduced to 85 µm. Consequently, this compensation setup can improve the accuracy of classical laser triangulation devices and make them more robust against changes in environmental conditions.

Transition from purely elastic to viscoelastic behavior of silica optical fibers at high temperatures characterized using regenerated Bragg gratings.

In this study, the response of regenerated fiber Bragg gratings (RFGBs) to axial forces was investigated in a temperature range from room temperature to 900 °C. For the first time, the transition from pure elastic to viscoelastic behavior around 700 °C of a standard SMF28 optical fiber was measured with an inscribed RFBG. An elastic model with linear temperature dependencies of Young's modulus and Poisson's ratio was established, and showed good agreement with the measurements up to temperatures of ∼500 °C. In the temperature range up to 900 °C, the RFBG response could be well described with a simple, single-material approach and a Burgers model that consists of a Kelvin and a Maxwell part. Based on the elastic parameter of the Maxwell part, the temperature-dependent force sensitivity of the RFBG was determined, and it showed a linear decrease in the range from room temperature to ∼500 °C, constant values in the range between ∼500 °C and ∼600 °C, and a strong increase at higher temperatures. While fulfilling the condition to operate in the elastic domain of the silica fiber, the investigations demonstrate that RFBGs can be used as force sensors up to temperatures of ∼600 °C - the range in which temperature-dependent force sensitivities have to be considered. The temperature-dependent parameters of the effective single-material model (elastic and viscoelastic part) are essential to describe the effective mechanical behavior of the optical fiber at high temperatures.

Shear-unlimited common-path speckle interferometer.

A single-aperture common-path speckle interferometer with an unlimited shear amount is developed. This unlimited shear amount is introduced when a Wollaston prism is placed near the Fourier plane of a common-path interferometer, which is built by using a quasi-${4f}$4f imaging system. The fundamentals of the shear amount and the spatial carrier frequency generation are analyzed mathematically, and the theoretical predictions are validated by a static experiment. Mode-I fracture experiments through the three-point bending are conducted to prove the feasibility and the capability of this method in full-field strain measurement with various shear amounts. A remarkable feature of this setup is that no tilt is required between the optical components to produce the unlimited shear amount in off-axis holography.