000118326 001__ 118326 000118326 005__ 20220916124048.0 000118326 037__ $$aTAZ-TFM-2022-202 000118326 041__ $$aeng 000118326 1001_ $$aMorilla Cabello, David 000118326 24200 $$aMulti-robot active perception for fast andefficient scene reconstruction. 000118326 24500 $$aMulti-robot active perception for fast andefficient scene reconstruction. 000118326 260__ $$aZaragoza$$bUniversidad de Zaragoza$$c2022 000118326 506__ $$aby-nc-sa$$bCreative Commons$$c3.0$$uhttp://creativecommons.org/licenses/by-nc-sa/3.0/ 000118326 520__ $$aThe efficiency of path-planning in robot navigation is crucial in tasks, such as search-and-rescue and disaster surveying, but this is emphasised even more when considering multi-rotor aerial robots due to the limited battery and flight time. In this spirit, this Master Thesis proposes an efficient, hierarchical planner to achieve a comprehensive visual coverage of large-scale outdoor scenarios for small drones. Following an initial reconnaissance flight, a coarse map of the scene gets built in real-time. Then, regions of the map that were not appropriately observed are identified and grouped by a novel perception-aware clustering process that enables the generation of continuous trajectories (sweeps) to cover them efficiently. Thanks to this partitioning of the map in a set of tasks, we are able to generalize the planning to an arbitrary number of drones and perform a well-balanced workload distribution among them. We compare our approach to an alternative state-of-the-art method for exploration and show the advantages of our pipeline in terms of efficiency for obtaining coverage in large environments.<br /> 000118326 521__ $$aMáster Universitario en Robótica, Gráficos y Visión por Computador 000118326 540__ $$aDerechos regulados por licencia Creative Commons 000118326 700__ $$aMontijano Muñoz, Eduardo$$edir. 000118326 700__ $$aChli, Margarita$$edir. 000118326 7102_ $$aUniversidad de Zaragoza$$bInformática e Ingeniería de Sistemas$$cIngeniería de Sistemas y Automática 000118326 8560_ $$f822899@unizar.es 000118326 8564_ $$s46046734$$uhttps://zaguan.unizar.es/record/118326/files/TAZ-TFM-2022-202.pdf$$yMemoria (eng) 000118326 909CO $$ooai:zaguan.unizar.es:118326$$pdriver$$ptrabajos-fin-master 000118326 950__ $$a 000118326 951__ $$adeposita:2022-09-16 000118326 980__ $$aTAZ$$bTFM$$cEINA 000118326 999__ $$a20220621130649.CREATION_DATE