The first video shows a tractor that selectively sprays the weed patches. The tractor trajectory, shown in the left bottom corner, was designed to cover the entire field and try the weed patches, represented in green, with a sprayer bar of 6 m long (12 nozzles). The second video shows two tractors that simultaneously and coordinately cover the same field by following parallel trajectories. The potential collisions during the turns on the headlands (see left bottom corner) are detected and solved by the Supervision System. ; A supervisor system for monitoring the operation of automated agricultural vehicles has been developed. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure such as pausing and resuming the vehicles while working. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system performs well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weeds treatments. The system is able to detect failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system is able to prevent collisions between vehicles by pausing/resuming the vehicles while working to avoid intersecting trajectories. ; Sponsorship: - RHEA: Robot fleets for highly effective agriculture and forestry management. Tipo proyecto: 7º Programa Marco; FP7-NMP-2009-LARGE-3, Grant Agreement: 245986; Duración: 2010-2014. - GroW: Sistema de inspección terrestre en vehículos autónomos y su aplicación efectiva a la detección de malas hierbas y su control localizado (GroW). Entidad Financiadora: MINECO, PLAN NACIONAL; AGL2011-30442-C02-02 Duración: 2012-2014. ; Peer reviewed


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    Titel :

    Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks



    Erscheinungsdatum :

    2015-02-17



    Medientyp :

    Audiovisuelles Material


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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