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相关论文: Precision Robotic Spot-Spraying: Reducing Herbicid…

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The advancements in precision agriculture are vital to support the increasing demand for global food supply. Precision spot spraying is a major step towards reducing chemical usage for pest and weed control in agriculture. A novel spot…

Modern herbicide application in agricultural settings typically relies on either large scale sprayers that dispense herbicide over crops and weeds alike or portable sprayers that require labor intensive manual operation. The former method…

Uniform and excessive herbicide application in modern agriculture contributes to increased input costs, environmental pollution, and the emergence of herbicide resistant weeds. To address these challenges, we developed a vision guided,…

Applying agrochemicals is the default procedure for conventional weed control in crop production, but has negative impacts on the environment. Robots have the potential to treat every plant in the field individually and thus can reduce the…

计算机视觉与模式识别 · 计算机科学 2018-06-12 Philipp Lottes , Jens Behley , Nived Chebrolu , Andres Milioto , Cyrill Stachniss

Smart weeding systems to perform plant-specific operations can contribute to the sustainability of agriculture and the environment. Despite monumental advances in autonomous robotic technologies for precision weed management in recent…

计算机视觉与模式识别 · 计算机科学 2021-12-30 Yayun Du , Guofeng Zhang , Darren Tsang , M. Khalid Jawed

In this article, we focus on the critical tasks of plant protection in arable farms, addressing a modern challenge in agriculture: integrating ecological considerations into the operational strategy of precision weeding robots like \bbot.…

机器人学 · 计算机科学 2024-07-08 Alireza Ahmadi , Michael Halstead , Claus Smitt , Chris McCool

Precision farming robots, which target to reduce the amount of herbicides that need to be brought out in the fields, must have the ability to identify crops and weeds in real time to trigger weeding actions. In this paper, we address the…

计算机视觉与模式识别 · 计算机科学 2018-03-05 Andres Milioto , Philipp Lottes , Cyrill Stachniss

Mobile robots are increasingly utilized in agriculture to automate labor-intensive tasks such as weeding, sowing, harvesting and soil analysis. Recently, agricultural robots have been developed to detect and remove weeds using mechanical…

Weed control is a critical challenge in modern agriculture, as weeds compete with crops for essential nutrient resources, significantly reducing crop yield and quality. Traditional weed control methods, including chemical and mechanical…

计算机视觉与模式识别 · 计算机科学 2025-02-11 Dingning Liu , Jinzhe Li , Haoyang Su , Bei Cui , Zhihui Wang , Qingbo Yuan , Wanli Ouyang , Nanqing Dong

The agriculture sector requires a lot of labor and resources. Hence, farmers are constantly being pressed for technology and automation to be cost-effective. In this context, autonomous robots can play a very important role in carrying out…

Organic weed control is a vital to improve crop yield with a sustainable approach. In this work, a directed energy weed control robot prototype specifically designed for organic farms is proposed. The robot uses a novel distributed array…

机器人学 · 计算机科学 2024-06-03 Deng Cao , Hongbo Zhang , Rajveer Dhillon

Uncontrolled growth of weeds can severely affect the crop yield and quality. Unrestricted use of herbicide for weed removal alters biodiversity and cause environmental pollution. Instead, identifying weed-infested regions can aid selective…

计算机视觉与模式识别 · 计算机科学 2021-02-22 Shantam Shorewala , Armaan Ashfaque , Sidharth R , Ujjwal Verma

Reducing the use of agrochemicals is an important component towards sustainable agriculture. Robots that can perform targeted weed control offer the potential to contribute to this goal, for example, through specialized weeding actions such…

计算机视觉与模式识别 · 计算机科学 2018-06-12 Philipp Lottes , Jens Behley , Andres Milioto , Cyrill Stachniss

Cultivation and weeding are two of the primary tasks performed by farmers today. A recent challenge for weeding is the desire to reduce herbicide and pesticide treatments while maintaining crop quality and quantity. In this paper, we…

机器人学 · 计算机科学 2024-12-04 Alireza Ahmadi , Michael Halstead , Chris McCool

Currently, weed control in commercial corn production is performed without considering weed distribution information in the field. This kind of weed management practice leads to excessive amounts of chemical herbicides being applied in a…

计算机视觉与模式识别 · 计算机科学 2025-01-28 Ranjan Sapkota , John Stenger , Michael Ostlie , Paulo Flores

Currently, weed control in a corn field is performed by a blanket application of herbicides which do not consider spatial distribution information of weeds and also uses an extensive amount of chemical herbicides. In order to reduce the…

图像与视频处理 · 电气工程与系统科学 2022-04-29 Ranjan Sapkota , Paulo Flores

The evolution of smaller, faster processors and cheaper digital storage mechanisms across the last 4-5 decades has vastly increased the opportunity to integrate intelligent technologies in a wide range of practical environments to address a…

计算机视觉与模式识别 · 计算机科学 2021-09-24 Adrian Salazar-Gomez , Madeleine Darbyshire , Junfeng Gao , Elizabeth I Sklar , Simon Parsons

Currently, weed control in a corn field is performed by a blanket application of herbicides that do not consider spatial distribution information of weeds and also uses an extensive amount of chemical herbicides. To reduce the amount of…

计算机视觉与模式识别 · 计算机科学 2022-06-07 Ranjan Sapkota , Paulo Flores

Italian ryegrass is a grass weed commonly found in winter wheat fields that are competitive with winter wheat for moisture and nutrients. Ryegrass can cause substantial reductions in yield and grain quality if not properly controlled with…

计算机视觉与模式识别 · 计算机科学 2024-10-31 Ishita Bansal , Peder Olsen , Roberto Estevão

Precision agriculture in general, and precision weeding in particular, have greatly benefited from the major advancements in deep learning and computer vision. A large variety of commercial robotic solutions are already available and…

计算机视觉与模式识别 · 计算机科学 2025-01-14 Paul Melki , Lionel Bombrun , Boubacar Diallo , Jérôme Dias , Jean-Pierre da Costa
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