Automatic identification of kinematic diagrams with computer vision

In this work, a computer vision algorithm for the detection and recognition of 2D kinematic diagrams, both from paper schemes and digital files, was developed. Furthermore, it runs even with hand-made diagrams, which can be correctly identified. The algorithm is mainly based on the use of the free computer vision library OpenCV, being able to identify each element of the kinematic diagram, its connection with the other elements and store its pixels, which will allow in future research the implementation of motion in the sketches themselves. Allowed elements are revolute, prismatic, fixed, cylindrical and rigid joints and rigid bars. The main applications of this work are focused on the teaching world, communication of ideas in a quickly and graphical way and for fast and preliminary designs of new mechanisms as people can draw the diagram in a Tablet or paper and simulate it in real time, avoiding the necessity to learn how to operate a specialized simulation software and the time it takes to prepare the virtual model and obtain its results

A benchmarking of commercial small fixed-wing electric UAVs and RGB cameras for photogrammetry monitoring in intertidal multi-regions

Small fixed-wing electric Unmanned Aerial Vehicles (UAVs) are perfect candidates to perform tasks in wide areas, such as photogrammetry, surveillance, monitoring, or search and rescue, among others. They are easy to transport and assemble, have much greater range and autonomy, and reach higher speeds than rotatory-wing UAVs. Aiming to contribute towards their future implementation, the objective of this article is to benchmark commercial, small, fixed-wing, electric UAVs and compatible RGB cameras to find the best combination for photogrammetry and data acquisition of mussel seeds and goose barnacles in a multi-region intertidal zone of the south coast of Galicia (NW of Spain). To compare all the options, a Coverage Path Planning (CPP) algorithm enhanced for fixed-wing UAVs to cover long areas with sharp corners was posed, followed by a Traveling Salesman Problem (TSP) to find the best route between regions. Results show that two options stand out from the rest: the Delair DT26 Open Payload with a PhaseOne iXM-100 camera (shortest path, minimum number of pictures and turns) and the Heliplane LRS 340 PRO with the Sony Alpha 7R IV sensor, finishing the task in the minimum time.Agencia Estatal de Investigación | Ref. PID2021-125060OB-I00Agencia Estatal de Investigación | Ref. TED2021-129756B-C31Ministerio de Universidades | Ref. FPU21/01176Universidade de Vig

Relative pose determination algorithm for space on-orbit close range autonomous operation using LiDAR

Non cooperative on-orbit operations, such as rendezvous, docking or berthing operations, have become more relevant, mainly due to the necessity of expanding mission lifetimes, the increase of space debris and the reduction of human dependency. In order to automate these operations, the relative pose calculation between the target and the chaser must be determined autonomously. In recent years, LiDAR sensors have been introduced for this problem, achieving good accuracies. The critical part of this operation is the first relative pose calculation, since there is no previous information about the attitude of the target. In this work, a methodology to carry out this first relative pose calculation using LiDAR sensors is presented. A template matching algorithm has been developed, which uses the 3D model of the target to calculate the relative pose of the target regarding the LiDAR sensor. Three different study cases, with different distances and rotations, have been simulated in order to validate the algorithm, reaching an average error of 0.0383m

Validation of Solid-State LiDAR Measurement System for Ballast Geometry Monitoring in Rail Tracks

The inspection and maintenance of track ballast are fundamental tasks for the preservation of the condition of railway networks. This work presents an application based on a low-cost solid-state LiDAR system, which allows the user to accurately measure the ballast geometry from a mobile inspection trolley or draisine. The solid-state LiDAR system, the LiVOX Avia, was validated on a test track through comparison with a traditional static LiDAR system, the Faro Focus 3D. The results show a standard deviation of around 6 mm for the solid-state LiDAR system. The LiVOX system also provides the capability to measure the ballast digital elevation model and profiles. The LiVOX results are in agreement with those obtained from the Faro Focus. The results demonstrate that the LiVOX system can sufficiently measure even the displacement of a single layer of ballast stones typically between 2.5 cm and 5 cm. The data provided can be easily digitalized using image processing tools and integrated into geographic information systems for infrastructure management