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Aerial coverage path planning applied to mapping

AuthorsValente, João
AdvisorBarrientos, Antonio ; Cerro, Jaime del
Issue Date21-Nov-2014
PublisherCSIC - Centro de Automática y Robótica (CAR)
Universidad Politécnica de Madrid
AbstractIn the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the o-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a eet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with dierent shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies dierent computational geometry approaches, providing a unique way to deal with workspaces with dierent shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-o and landing positions as well as a safety distance between elements of the eet. Moreover, it has to avoid forbidden zones to y. Three dierent algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of eld experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the ndings attained from this thesis improve ACPP mission for mapping purpose in an ecient and safe manner.
DescriptionTesis Doctoral defendida para la obtención del Título de Grado de Doctor. xvi, 165 p. : il., fot., diagr. Fecha de defensa de la Tesis Doctoral: 21 de noviembre de 2014
Appears in Collections:(CAR) Tesis
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