Autonomous Aerial Mapping and Observation Task for IMAV2014 CompetitionReport as inadecuate




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1 MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l-Aérien 2 LAAS-RIS - Équipe Robotique et InteractionS LAAS - Laboratoire d-analyse et d-architecture des systèmes Toulouse 3 DRONES - ENAC - Programme transverse Drones ENAC - Ecole Nationale de l-Aviation Civile

Abstract : The IMAV2014 Competition gives an important place to computer vision and aerial mapping. This paper presents the different strategies and algorithms that have been developed in order to tackle these particular problems. The first task consists in automatically reading the digit displayed by a seven segment panel on the front wall of a building. Robust algorithms for segments detection are used in order to extract the features from the scene. The second task requires to produce an aerial map of the competition place. In order to generate a coherent composite image, photogrammetry methods are used, including interest points pairing and bundle adjustment. We propose to mix 3D mapping methods and standard 2D image mosaicking in order to achieve the processing in the time available during the competition while obtaining an geometrically consistent map.

keyword : IMAV2014 MAV Micro Air Vehicle autonomous aerial mapping observation task IMAV2014 competition





Author: Emmanuel Colles - Fabien Nollet - Bertrand Vandeportaele - Gautier Hattenberger -

Source: https://hal.archives-ouvertes.fr/



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