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Book chapter

Validation of Automated Farming

In Validation and Verification of Automated Systems — 2020, pp. 271-295
From

TTTech Computertechnik AG1

University of Las Palmas de Gran Canaria2

Creanex Oy3

TECNALIA4

FZI Forschungszentrum Informatik5

Intituto Tencologico de Informatica6

Instituto Superior de Engenharia do Porto7

CHEC Research Centre, Department of Chemical and Biochemical Engineering, Technical University of Denmark8

Department of Chemical and Biochemical Engineering, Technical University of Denmark9

This chapter presents first concepts for the improved validation of automated farming solutions. Within the ENABLE-S3 ECSEL JU project, the farming use case team presents developments within the agricultural domain, that can in the future improve the life and working environment of farmers. Applications such as autonomous driving of farming vehicles equipped with sensors and drones supporting hyperspectral cameras, validated by newly defined testing systems like co-simulation of farming vehicles, model-based simulation of farming systems and verification and testing of in-vehicle communication are advances developed during the project.

As agricultural activities are very dependent on environmental parameters (e.g. weather, harvest ripeness) and the availability of the actual vehicles (which is very often not the case), the use case team opted for realistic simulators for first validation approaches. In this work, multiple simulators are introduced that combine many agricultural concepts including the simulation of the farming systems (i.e. harvester, tractors and drones).

Additionally, introducing autonomy into vehicles requires deterministic in-vehicle communication and the guarantee that messages arrive timely. Validation of in-vehicle communication is introduced to showcase the applicability of the technology. The overall goal of the work performed in this use case is to reduce the testing costs and time of farming scenarios, be less dependent on many factors (like crop availability) and be able to perform continuous validation and verification of the farming systems.

Language: English
Publisher: Springer
Year: 2020
Pages: 271-295
Journal subtitle: Results of the Enable-s3 Project
ISBN: 3030146278 , 3030146286 , 9783030146276 and 9783030146283
Types: Book chapter
DOI: 10.1007/978-3-030-14628-3_20
ORCIDs: Zhao, Liyan

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