View in EDS

Advanced Control Subsystem for Mobile Robotic Systems in Precision Agriculture

Saved in:
Bibliographic Details
Title: Advanced Control Subsystem for Mobile Robotic Systems in Precision Agriculture
Authors: Marius Pandelea, Gidea Mihai, Mihaiela Iliescu, Luige Vladareanu
Source: International Journal of Robotics and Automation Technology. 9:8-16
Publisher Information: Zeal Press, 2025.
Publication Year: 2025
Subject Terms: 2. Zero hunger, 0209 industrial biotechnology, 02 engineering and technology
Description: This concept paper presents Mobile Agricultural Robots (MARs) for the development of precision agriculture and implicitly the smart farms through knowledge, reason, technology, interaction, learning and validation. Finding new strategies and control algorithms for MARs has led to the design of an Autonomous Robotic Platform Weed Control (ARoPWeC). The paradigm of this concept is based on the integration of intelligent agricultural subsystems into mobile robotic platforms. For maintenance activities in case of hoeing crops (corn, potatoes, vegetables, vineyards), ARoPWeC benefits from the automatic guidance subsystem and spectral analysis subsystem for differentiation and classification of the weeds. The elimination of weeds and pests is done through the Drop-on-Demand spray subsystem with multi-objective control, and for increasing efficiency through the Deep Learning subsystem.
Document Type: Article
ISSN: 2409-9694
DOI: 10.31875/2409-9694.2022.09.02
Accession Number: edsair.doi...........6fa2eaf71eca534cca838b86b4e43cd6
Database: OpenAIRE
Description
Abstract:This concept paper presents Mobile Agricultural Robots (MARs) for the development of precision agriculture and implicitly the smart farms through knowledge, reason, technology, interaction, learning and validation. Finding new strategies and control algorithms for MARs has led to the design of an Autonomous Robotic Platform Weed Control (ARoPWeC). The paradigm of this concept is based on the integration of intelligent agricultural subsystems into mobile robotic platforms. For maintenance activities in case of hoeing crops (corn, potatoes, vegetables, vineyards), ARoPWeC benefits from the automatic guidance subsystem and spectral analysis subsystem for differentiation and classification of the weeds. The elimination of weeds and pests is done through the Drop-on-Demand spray subsystem with multi-objective control, and for increasing efficiency through the Deep Learning subsystem.
ISSN:24099694
DOI:10.31875/2409-9694.2022.09.02