Fundamental parameters modeling for the lunar telescope

The powerful flow of highly accurate and multiparameter information produced by spacecrafts has caused a surge interest in the industrial robotic exploration of the Moon and manned flight to Mars after the creation of long-term lunar bases. The modern level of both ongoing and planned lunar studies is characterized by a high level of observation accuracy and a large variety of observation methods. The study of the Moon’s rotational parameters (MRP) is of important value. For this reason, new methods for analyzing big data sets on observation of MRP and extracting the highest possible amount of scientific information from them are needed. Such space technologies require the creation of in-situ telescopes on the Moon. The long-term laser measurements have supplied comprehensive observational information about the Moon. This allows for a description of the Moon’s dynamics with the accuracy required at the current stage - the error of determining the distance to the Moon should be less than a meter, while the one of establishing rotational parameters - arc milliseconds. Nevertheless, there is a necessity to obtain observation data independent of laser measurements. One of the ways to do it is to place on the lunar surface one or several optical telescopes, that will allow determining lunar rotational parameters by measuring the trajectories of the stars and will also be used to solve astrophysical and astrometric problems in the future. This work considers the results of computer modeling of observations taken by lunar in-situ telescopes located at various selenographic latitudes. The sensitivity of MRP to the observed selenographic coordinates of the stars is assessed. Based on the analysis of the simulation results, the optimum location of the telescope is concluded to be at a latitude of 30–45°. The constructive suggestions on the described experiment’s implementation are presented in the paper. The details that will allow implementing or declining the practical implementation of the in-situ telescope are discussed.

PSXVI-20 Real-time localization system for dairy cattle in a commercial facility: Evaluation of dynamic positioning ability

Real-time location tracking of dairy cattle on commercial facilities enables producers to quickly locate and tend to cows and provides insight into health status and animal welfare. The effectiveness of these systems depends on accurate and reliable reporting of information. Therefore, this experiment’s objective was to assess the dynamic positioning abilities of a commercially available real-time location ear tag system (SmartBow; Zoetis, Parsippany, NJ) for use in group-housed dairy cattle. Using 2 pens of a freestall barn, cameras (n = 18) were installed on barn fixtures and positioned to photograph cow usage of feedbunk (n = 4), stall (n = 10), or waterer (n = 4). Photographs were captured automatically at 1-min intervals for 85 hours, consecutively. Laser measurements determined X and Y coordinates for reference point locations respective to camera. In dynamic position assessments, variations in ear tag proximity to measured reference points are to be expected. One trained observer reviewed photographs, saving only those depicting cows with visible farm-assigned ID. Data points were only defined if farm-assigned ID was associated with an active technology ear tag. For data analyses, technology-reported X and Y coordinates of data points were compared to reference point locations. Of all data points (n = 114,633), mean distance error was 3.82 m (SD= 6.73 m). Median distance error was 2.44 m (SD= 6.73; Q1= 1.41 m; Q3=5.13 m). With removal of outliers (99th percentile), data (n = 113,487) had a mean distance error of 3.82 m (min= 0.01 m; max= 33.80 m) and a median of 2.41 m (SD= 2.78 m; Q1= 1.40 m; Q3= 4.95 m). Using distance error, mean percentages of data points that fell within specified radii of circles centered about reference point locations were calculated (Table 1). These results suggest that this ear tag technology can accurately report the dynamic positions of dairy cattle moving freely in a commercial freestall barn environment.

High Speed PIV Measurements in Water Hammer

An experimental study addressing the challenge to measure relaxation coefficient of very fast phenomena such as water hammers is presented. An acrylic projectile containing water is accelerated and impacts a metal wall creating a water hammer. State of the art laser measurements techniques will be deployed in order to achieve such goal. A compressed air custom built cannon is used to accelerate the projectile and create the impact leading to the water hammer. First experimental results for Shadowgraphy and PIV measurements are presented and discussed with focus on the future development for the presented facility.

AUTOMATIC SEGMENTATION OF POINT CLOUDS IN THE ARCHITECTURE ENVIRONMENT

Correct and reliable identification and classification of different structures and infrastructures that make up a city (e.g. residential buildings, school buildings, hospitals, power stations, routes of communication, etc.) are of great importance for the AEC/FM (Architecture, Engineering, Construction, and Facilities Management) domain and for seismic risk assessments, among others. For decades, the method of collecting buildings information has been through field campaigns. This practice requires significant resources in terms of qualified engineers or architects to identify the geometry of the different elements that constitute the structure, building materials and construction processes. Nowadays, there are different geospatial techniques that allow data acquisition on a massive scale in a short period of time. In particular, by means of laser measurements, it is possible to have clouds of millions of points with geometric and radiometric information in a matter of seconds. In this article, we present ABM-indoor, a LIDAR-based approach that automatically provides a three-dimensional models of buildings in vector format. Models include floors, ceilings, walls (up to five dominant directions), columns, elements located on floors and elements hanging from ceilings. Efforts are underway to transfer this model to a Building Information Model (BIM).

Study on Real-Time Point Cloud Superimposition on Camera Image to Assist Environmental Three-Dimensional Laser Scanning

Recently, three-dimensional (3D) laser scanning technology using terrestrial laser scanner (TLS) has been widely used in the fields of plant manufacturing, civil engineering and construction, and surveying. It is desirable for the operator to be able to immediately and intuitively confirm the scanned point cloud to reduce unscanned regions and acquire scanned point clouds of high quality. Therefore, in this study, we developed a method to superimpose the point cloud on the actual environment to assist environmental 3D laser measurements, allowing the operator to check the scanned point cloud or unscanned regions in real time using the camera image. The method included extracting the correspondences of the camera image and the image generated by point clouds by considering unscanned regions, estimating the camera position and attitude in the point cloud by sampling correspondence points, and superimposing the scanned point cloud and unscanned regions on the camera image. When the proposed method was applied to two types of environments, that is, a boiler room and university office, the estimated camera image had a mean position error of approximately 150 mm and mean attitude error of approximately 1°, while the scanned point cloud and unscanned regions were superimposed on the camera image on a tablet PC at a rate of approximately 1 fps.

Mapping Arctic Sea Ice Surface Roughness with Multi-angle Imaging SpectroRadiometry

<p>Surface roughness is a crucial parameter in climate and oceanographic studies, constraining momentum transfer between the atmosphere and ocean, providing preconditioning for summer melt pond extent, while also closely related to ice age. High resolution roughness estimates from airborne laser measurements are limited in spatial and temporal coverage while pan-Arctic satellite roughness have remained elusive and do not extended over multi-decadal time-scales. The MISR (Multi-angle Imaging SpectroRadiometer) instrument acquires optical imagery at 275m (red channel) and 1.1 km (all channels) resolutions from nine near-simultaneous camera view zenith angles sampling specular anisotropy, since 1999. Extending on previous work to model sea ice surface roughness from MISR angular reflectance signatures, a training dataset of cloud-free pixels and coincident roughness is generated. Surface roughness, defined as the standard deviation of the within-pixel elevations to a best-fit plane, is modelled using several techniques and Support Vector Regression with a Radial Basis Function kernel selected. Hyperparameters are tuned using grid optimisation, model performance is assessed using nested cross-validation, and product performance is assessed with independent validation. We present a derived sea ice roughness product at 1.1km resolution over a two-decade timespan (1999 – 2020) and a corresponding time series analysis by region. These show considerable promise in detecting newly formed smooth ice from polynyas, and detailed surface features such as ridges and leads. </p>