Low-Cost Robot for Agricultural Image Data Acquisition

Vasconcelos, Gustavo J. Q.; Costa, Gabriel Schubert Ruiz; Spina, Thiago Vallin; Pedrini, Hélio

doi:10.3390/agriculture13020413

Cited by 12 publications

(10 citation statements)

References 27 publications

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“…Thus, the approach and the research presented in this paper provide an original solution (new application of the FPA and different design method of the kinematic chain). Robotic platforms are becoming very popular tools in different fields-they can be used in warehouse and delivery tasks, and also in agriculture [28], mining [29] and general monitoring designs. The main disadvantage of most robot applications is their ability to travel only on flat surfaces, without the possibility of moving over or around obstacles.…”

Section: State-of-the-art and Related Workmentioning

confidence: 99%

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

Malarczyk,

Kaczmarczyk,

Szrek

et al. 2023

Future Internet

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This paper presents the operation of a remotely controlled, wheel-legged robot. The developed Wi-Fi connection framework is established on a popular ARM microcontroller board. The implementation provides a low-cost solution that is in congruence with the newest industrial standards. Additionally, the problem of limb structure and motor speed control is solved. The design process of the mechanical structure is enhanced by a nature-inspired metaheuristic optimization algorithm. An FOC-based BLDC motor speed control strategy is selected to guarantee dynamic operation of the drive. The paper provides both the theoretical considerations and the obtained prototype experimental results.

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Section: State-of-the-art and Related Workmentioning

confidence: 99%

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

Malarczyk,

Kaczmarczyk,

Szrek

et al. 2023

Future Internet

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“…This paper studies an automated weeding system using manipulators for irregularly planted crops in the field. Various automated-weeding methods exist, but the primary tasks in weeding include: (1) the detection of the weeds to be removed and (2) guiding the weeding mechanism to those weeds [9]. As weeds and weeding periods differ depending on several factors, such as the type of crop plant, cultivation method, and environmental conditions, general-purpose weed detection is difficult [10].…”

Section: Introductionmentioning

confidence: 99%

Automated Weeding Systems for Weed Detection and Removal in Garlic / Ginger Fields

Nakabayashi,

Yamagishi,

Suzuki

2024

IJACSA

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The global agriculture industry has faced various problems, such as rapid population growth and climate change. Among several countries, Japan has a declining agricultural workforce. To solve this problem, the Japanese government aims to realize "Smart agriculture" that applies information and communication technology, artificial intelligence, and robotics. Smart agriculture requires the development of robot technology to perform weeding and other labor-intensive agricultural tasks. Robotic weeding consists of an object detection method using machine learning to classify weeds and crops and an autonomous weeding system using robot hands and lasers. However, the approach used for these methods changes depending on the crop growth. The weeding system must consider the combination according to crop growth. This study addresses weed detection and autonomous weeding in crop-weed mixed ridges, such as garlic and ginger fields. We first develop a weed detection method using Mask R-CNN, which can detect individual weeds by instance segmentation from color images captured by an RGB-D camera. The proposed system can obtain weed coordinates in physical space based on the detected weed region and the depth image captured by the camera. Subsequently, we propose an approach to guide the weeding manipulator toward the detected weed coordinates. This paper integrates weed detection and autonomous weeding through these two proposed methods. We evaluate the performance of the Mask R-CNN trained on images taken in an actual field and demonstrate that the proposed autonomous weeding system works on a reproduced ridge with artificial weeds similar to garlic and weed leaves.

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“…Work on these complex tasks is greatly facilitated in the use of machine vision and decision-making [3].…”

Section: Introductionmentioning

confidence: 99%

3d Model of the Mechanical Part of a Weed Recognition System in an Agricultural Robot in 3d Experience Environment

Kehayov,

Ivanov,

Komitov

2024

ETR

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The damage from weeds in the cultivation of agricultural crops is ubiquitous and they adversely affect the yields of agricultural production. The soil conditions of the places where the crops are grown deteriorate. Contribute to the development of diseases and the enemies on them. Apart from this, it is difficult to carry out mechanized processing and harvesting activities. Weeds also worsen the very quality of the harvested produce. That is why the availability of a recognition system to the agricultural robot is essential to reduce the adverse influence. It is part of a system of control and destruction. In this weed recognition system, an essential element is a robotic arm to enable a camera to perform video surveillance.The aim of this paper is to modelling only the mechanical anchorage system for weed recognition elements that it does not interfere with the other elements with which it interacts. To be as effective as possible, this system must be as close as possible to the plants and at the same time close to the weed eradication system in agricultural robot.A three-dimensional model of the weed recognition mechanical parts from system is discussed in the paper. It is designed in a 3D Experience environment, taking into account the parameters necessary for the movement of the system. Strength sizing of the structure and working simulations of the model were made.

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Low-Cost Robot for Agricultural Image Data Acquisition

Cited by 12 publications

References 27 publications

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

Automated Weeding Systems for Weed Detection and Removal in Garlic / Ginger Fields

3d Model of the Mechanical Part of a Weed Recognition System in an Agricultural Robot in 3d Experience Environment

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