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Active UAV payload based on horizontal propellers for contact inspections tasks

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Active UAV payload based on horizontal propellers for contact inspections tasks

González De Santos, Luis Miguel; Martínez Sánchez, Joaquín; González Jorge, Higinio; Arias Sánchez, Pedro
 
DATE : 2020-12
UNIVERSAL IDENTIFIER : http://hdl.handle.net/11093/1529
UNESCO SUBJECT : 2504 Geodesia
DOCUMENT TYPE : article

ABSTRACT :

Increase in building complexity can cause difficulties orienting people, especially people with reduced mobility. This work presents a methodology to enable the direct use of indoor point clouds as navigable models for pathfinding. Input point cloud is classified in horizontal and vertical elements according to inclination of each point respect to n neighbour points. Points belonging to the main floor are detected by histogram application. Other floors at different heights and stairs are detected by analysing the proximity to the detected main floor. Then, point cloud regions classified as floor are rasterized to delimit navigable surface and occlusions are corrected by applying morphological operations assuming planarity and taking into account the existence of obstacles. Finally, point cloud of navigable floor is downsampled and structured in a grid. Remaining points are nodes to create navigable indoor graph. The methodology has been tested in two real case studies provided by the ISPRS benchmark on indoor modelling. A pathfinding algorithm is applied to generate routes and to ... [+]
Increase in building complexity can cause difficulties orienting people, especially people with reduced mobility. This work presents a methodology to enable the direct use of indoor point clouds as navigable models for pathfinding. Input point cloud is classified in horizontal and vertical elements according to inclination of each point respect to n neighbour points. Points belonging to the main floor are detected by histogram application. Other floors at different heights and stairs are detected by analysing the proximity to the detected main floor. Then, point cloud regions classified as floor are rasterized to delimit navigable surface and occlusions are corrected by applying morphological operations assuming planarity and taking into account the existence of obstacles. Finally, point cloud of navigable floor is downsampled and structured in a grid. Remaining points are nodes to create navigable indoor graph. The methodology has been tested in two real case studies provided by the ISPRS benchmark on indoor modelling. A pathfinding algorithm is applied to generate routes and to verify the usability of generated graphs. Generated models and routes are coherent with selected motor skills because routes avoid obstacles and can cross areas of non-acquired The present work presents a UAV payload designed to perform semi-autonomous contact inspection tasks in vertical structures. The presented system includes on-board positioning capabilities to calculate the distance and angle between the structure and the UAV. In this way, the system is able to navigate in the neighbourhood of the structure, that may be considered a GPS-denied area. The payload includes two horizontal propellers aimed to push the system against the structure gently. The distance and angle acquired by the payload controller are a basis to calculate the control signals for payload engines and UAV heading. Such control signals are needed to perform the contact. Also, the proposed system has been compared to a previous design based on the UAV pitch signal control, highlighting the advantages of the new prototype. The series of tests that have been performed on the system demonstrate that the developed payload maintains a more stable and reliable contact with the structure. [-]

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