In the last years, unmanned aerial vehicles are becoming a reality in the context of precision agriculture, mainly for monitoring, patrolling and remote sensing tasks, but also for 3D map reconstruction. In this paper, we present an innovative approach where a fleet of unmanned aerial vehicles is exploited to perform remote sensing tasks over an apple orchard for reconstructing a 3D map of the field, formulating the covering control problem to combine the position of a monitoring target and the viewing angle. Moreover, the objective function of the controller is defined by an importance index, which has been computed from a multi-spectral map of the field, obtained by a preliminary flight, using a semantic interpretation scheme based on a convolutional neural network. This objective function is then updated according to the history of the past coverage states, thus allowing the drones to take situation-adaptive actions. The effectiveness of the proposed covering control strategy has been validated through simulations on a Robot Operating System. Copyright (C) 2022 The Authors.


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    Title :

    3D Map Reconstruction of an Orchard using an Angle-Aware Covering Control Strategy


    Contributors:
    Mammarella, M (author) / Donati, C (author) / Shimizu, T (author) / Suenaga, M (author) / Comba, L (author) / Biglia, A (author) / Uto, K (author) / Hatanaka, T (author) / Gay, P (author) / Dabbene, F (author)

    Publication date :

    2022-01-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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