Tool management, controlling and condition detection for highly automated/autonomous soil cultivation

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Highly automated and autonomous agricultural machines have the potential to perform field work with a minimum of energy and manpower. For the application case of tillage, sowing and weed control, important tool-specific challenges are the precise and variable depth control of the tools, the identification of the tool conditions in the field and, in the application case of an automated tool change, systems for identifying the tools and the working equipment. To meet all these requirements, the machines need a smart tool control systems. These functionalities are integrated into the highly flexible and modular machine concept-Feldschwarm1. The depth control is able to guide the tool at a defined working depth, thus guaranteeing the desired results and requiring a minimum of fuel consumption. The tool recognition works without contact. The tools have a memory device with a special set of parameters, for example the identification of the tool, the range of optimal working depth and, in case of an active tool, the nominal speed range. A camera system is used to identify the tool conditions. It detects wear, misalignment and loss of tools. The wear values are used to adjust the depth control and stored on the tool memory device.

Details

OriginalspracheEnglisch
TitelLAND.TECHNIK 2020
Herausgeber (Verlag)VDI Verlag, Düsseldorf
Seiten73-82
Seitenumfang10
ISBN (elektronisch)978-3-18-102374-7
ISBN (Print)978-3-18-092374-1
PublikationsstatusVeröffentlicht - 2020
Peer-Review-StatusJa

Publikationsreihe

ReiheVDI Berichte
Nummer2374
Band2020
ISSN0083-5560

Konferenz

Titel78th International Conference on Agricultural Engineering
UntertitelThe Forum for Agricultural Engineering Innovations
KurztitelLAND.TECHNIK 2020
Veranstaltungsnummer78
Dauer3 - 4 November 2020
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtOnline
StadtVirtual, Online
LandDeutschland

Externe IDs

Scopus 85105806468

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

ASJC Scopus Sachgebiete

Schlagwörter

  • Agricultural robots, Automation, Feldschwarm, Tool management, Wear detection