Overview of Mechatronic Design for a Weed-Management Robotic System #

Pérez, Tristán; Bawden, Owen; Kulk, Jason; Russell, Raymond; McCool, Christopher; English, Andrew; Dayoub, Feras

doi:10.1201/9781315203638-2

Cited by 2 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Automated and robotic techniques facilitate the operator's work, reduce labor time costs, and increase the efficiency of mechanical weeding compared to conventional weed control methods [17]. In addition, the smaller dimensions and weights of robots compared to traditional heavy tractors result in lower soil compaction [38][39][40].…”

Section: Ecological Weed Control Methodsmentioning

confidence: 99%

Influence of Mechanical and Intelligent Robotic Weed Control Methods on Energy Efficiency and Environment in Organic Sugar Beet Production

et al. 2021

View full text Add to dashboard Cite

Rapidly warming climate, tightening environmental requirements, an aging society, rising wages, and demand for organic products are forcing farming to be more efficient and sustainable. The main aim of this study was to perform an analytical analysis and to determine the energy use and GHG emissions of organic sugar beet production using different weed control methods. Seven different methods of non-chemical weed control were compared. Mechanical inter-row loosening, inter-row cutting and mulching with weeds, weed smothering with catch crops, and thermal inter-row steaming were performed in field experiments at the Experimental Station of Vytautas Magnus University (Lithuania, 2015–2017). The other three, namely, automated mechanical inter-row loosening with cameras for row-tracking, inter-row loosening with a diesel-powered robot, and inter-row loosening with an electric robot were calculated analytically. The results showed that the average total energy use of organic sugar beet production was 27,844 MJ ha−1, of which manure costs accounted for 48–53% and diesel fuel for 29–35%. An average energy efficiency ratio was 7.18, while energy productivity was 1.83 kg MJ ha−1. Analysis of GHG emissions showed that the total average GHG emissions to the environment from organic sugar beet production amounted to 4552 kg CO2eq ha−1, and the average GHG emissions ratio was 4.47. The most sustainable organic sugar beet production was achieved by using mechanical inter-row loosening with a diesel-powered robot for weed control.

show abstract

Section: Ecological Weed Control Methodsmentioning

confidence: 99%

Influence of Mechanical and Intelligent Robotic Weed Control Methods on Energy Efficiency and Environment in Organic Sugar Beet Production

et al. 2021

View full text Add to dashboard Cite

show abstract

“…No campo da robótica agrícola, diversos sistemas foram desenvolvidos nas últimas décadas (Tian, 2002;Perez et al, 2017;Ahlin et al, 2017). Esses estudos desenvolveram dispositivos que buscam, entre outros, auxiliar na colheita, plantio e pulverização de fertilizantes ou agrotóxicos.…”

Section: Introdu ç ãOunclassified

Sistema de navegação autônoma para o robô agrícola Soybot

Martins

Carvalho

Ramos

et al. 2021

Procedings Do XV Simpósio Brasileiro De Automação Inteligente

View full text Add to dashboard Cite

The autonomy of agricultural machines has been an important research field for Precision Agriculture. With the use of global positioning systems (GPS), the farmer is able to maximize the yield of his land through precise sowing. For other machines to perform actions after planting, the farmer often does not have data on the exact location of each row of the plantation; therefore, just being guided by the global position is not enough. The present work proposes an approach consisting of two steps for the control of the Soybot agricultural robot: a computer vision technique for the robot to travel through the interior of a grown plantation, without damaging it; and a path planning technique so that, at the end of the plantation row, it enters in the next row. Resumo: A autonomia de máquinas agrícolas tem sido uma área de pesquisa importante para a Agricultura de Precisão. Com a utilização de sistemas de posição global (GPS), o fazendeiro consegue maximizar o rendimento de seu terreno por meio de um semeio preciso. Para que outras máquinas realizem ações após o plantio, muitas vezes o fazendeiro não possui dados da localização exata de cada fileira da plantação; logo, se guiar apenas pela posição global não é suficiente. O presente trabalho propõe uma abordagem composta por dois passos para o controle do robô agrícola Soybot: uma técnica por visão computacional para que o robô percorra o interior de uma plantação crescida, sem danificá-la; e uma técnica de planejamento de caminho para que este, ao final de uma fileira percorrida na plantação, manobre e entre na próxima fileira.

show abstract

Overview of Mechatronic Design for a Weed-Management Robotic System #

Cited by 2 publications

References 2 publications

Influence of Mechanical and Intelligent Robotic Weed Control Methods on Energy Efficiency and Environment in Organic Sugar Beet Production

Influence of Mechanical and Intelligent Robotic Weed Control Methods on Energy Efficiency and Environment in Organic Sugar Beet Production

Sistema de navegação autônoma para o robô agrícola Soybot

Contact Info

Product

Resources

About