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Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV)

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Abstract

The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. The simulation and experimental results show the validity and effectiveness of the proposed algorithm.

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... Over the past few decades, UAVs have been widely used in military and civilian applications [24]. The UAVs can be used for search and rescue [25,26], photogrammetry [27,28], structures inspection [29,30], model reconstruction [31,32], smart farming [33,34], post-earthquake assessment [35] etc. Many of these UAVs applications involve Coverage Path Planning (CPP) technique, which requires building a path that guarantees that an agent will explore every location in a given scenario [36] . ...
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... There are many kinds of UAV missions, resulting in different types of UAV planning problems. Well-known problems including but not limited to the UAV mission and payload optimization [2,21], UAV routing and obstacle avoidance [6,16], regional searching and coverage [1,31], target tracking and assessment [15,37] and UAVs formation control [12,13]. In addition to those isuues, another practical problem that addresses the UAV routing and orientation under inaccurate but correctable navigation environments should also be underlined. ...
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In this paper, we study the time-optimal trajectory planning of a sensor attached to an unmanned aerial vehicle (UAV) to provide complete 3-dimensional coverage with applications to urban environments with 2.5-dimensional features. The basic approach is to approximate the features of interest with a set of non planar coverage surfaces and to design a motion plan that guarantees the coverage surface is swept completely with a conical-field-of-view sensor. We establish a lower bound on time for a UAV to achieve complete coverage and derive the analytical coverage plan whose duration is a constant times this lower bound. Our hardware-in-the-loop simulation results verify the effectiveness of the proposed algorithm.
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This paper presents a model-based view planning approach for automated object reconstruction or inspection using laser scanning range sensors. Quality objectives and performance measures are defined. Camera and positioning systems performance is modeled statistically. A theoretical framework is presented. The method is applicable to a broad class of objects with reasonable geometry and reflectance properties. Sampling of object surface and viewpoint space is characterized, including measurement noise and poses error effects. The technique is generalizable for common range camera and positioning system designs. Le document présente une méthode de planification de vues basée sur un modèle pour la reconstitution et l'inspection automatique des objets à l'aide de capteurs de distance à balayage laser. Les objectifs de qualité et les mesures de rendement y sont décrits. Le rendement des systèmes de positionnement et de caméra est modélisé par méthode statistique. Un cadre théorique est présenté dans le document. La méthode peut être appliquée à une vaste gamme d'objets présentant une géométrie et des propriétés de réflectance raisonnables. Un échantillonnage de la surface de l'objet et de l'espace observé est caractérisé; les données comprennent entre autre la mesure du bruit et des effets des erreurs de pose. La technique peut s'appliquer de façon générale à la conception des systèmes courants de positionnement et de caméras télémétriques.
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