A robot platform for unmanned weeding in a paddy field using sensor fusion

Kim, Gook-Hwan; Kim, Sang-Cheol; Hong, Yeh-Sun; Han, Kil-Su; Lee, Soon-Geul

doi:10.1109/coase.2012.6386466

Cited by 13 publications

(4 citation statements)

References 11 publications

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“…However, they achieved higher accuracy (98.2%) after combining RGB + LIDAR data. Kim et al (2012) could successfully navigate an unmanned weeding robot using sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). The robot also needs more sophisticated and intelligent algorithms to accomplish different subtasks such as sensing, navigation, pathplanning, and control.…”

Section: Sensors and Controllers Fusion Technique Can Improve The Performance Of Robotmentioning

confidence: 99%

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Atefi

Pitla

et al. 2021

Front. Plant Sci.

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Phenotyping plants is an essential component of any effort to develop new crop varieties. As plant breeders seek to increase crop productivity and produce more food for the future, the amount of phenotype information they require will also increase. Traditional plant phenotyping relying on manual measurement is laborious, time-consuming, error-prone, and costly. Plant phenotyping robots have emerged as a high-throughput technology to measure morphological, chemical and physiological properties of large number of plants. Several robotic systems have been developed to fulfill different phenotyping missions. In particular, robotic phenotyping has the potential to enable efficient monitoring of changes in plant traits over time in both controlled environments and in the field. The operation of these robots can be challenging as a result of the dynamic nature of plants and the agricultural environments. Here we discuss developments in phenotyping robots, and the challenges which have been overcome and others which remain outstanding. In addition, some perspective applications of the phenotyping robots are also presented. We optimistically anticipate that autonomous and robotic systems will make great leaps forward in the next 10 years to advance the plant phenotyping research into a new era.

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Section: Sensors and Controllers Fusion Technique Can Improve The Performance Of Robotmentioning

confidence: 99%

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Atefi

Pitla

et al. 2021

Front. Plant Sci.

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“…In order to remove the weeds by mechanical means, the system should first detect the row that it will work on, and then cut or pluck out the weeds. The precision in row detection recorded with mechanical weeding robots was less than 25 mm [23,24], followed by other systems with precision less than 6 mm, [25,26] or higher, up to 3 cm [27,28]. In addition, the performance of the weed removal (expressed also as weeding efficiency) has been evaluated in systems that presented rates higher than 90% [24,29], and 65% and 82%-for two different presented methods [30].…”

Section: Weeding Robotic Systemsmentioning

confidence: 99%

Agricultural Robotics for Field Operations

Fountas

Mylonas

Malounas

et al. 2020

Sensors

213

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Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.

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“…The advancement of imaging technologies has provided a great opportunity to sense and create 2D, 3D, and 4D (spatial + temporal) images of plants [24]. Technologies to obtain 2D, 3D and 4D perception of the environment has been achieved using the following sensors in agricultural fields; visible light, near-infrared, thermal, fluorescence, spectroscopy, structural topography imaging, fluorescence, digital imaging (RGB), multispectral, color infrared, hyperspectral, thermal, spectroradiometer, spectrometer, 3D cameras, moisture, pH, light-reflective, light detection and ranging (LIDAR), sound navigation and ranging (SONAR), ground-penetrating radar and electrical resistance tomography [24][25][26][27][28][29][30] Other sensors, such as potentiometers, inertial, mechanical, ultrasonic, optical encoder, RF receiver, piezoelectric rate, Near Infrared (NIR), laser range finder (LRF), Geomagnetic Direction Sensor (GDS), Fiber Optic Gyroscope (FOG), piezoelectric yaw, pitch and roll rate, acoustic and Inertial Measurement Units (IMUs) have been used to provide direction of the robot and navigation feedback [7,[31][32][33].…”

Section: Agricultural Robot Sensingmentioning

confidence: 99%

An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting

et al. 2020

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In this review, we examine opportunities and challenges for 21st-century robotic agricultural cotton harvesting research and commercial development. The paper reviews opportunities present in the agricultural robotics industry, and a detailed analysis is conducted for the cotton harvesting robot industry. The review is divided into four sections: (1) general agricultural robotic operations, where we check the current robotic technologies in agriculture; (2) opportunities and advances in related robotic harvesting fields, which is focused on investigating robotic harvesting technologies; (3) status and progress in cotton harvesting robot research, which concentrates on the current research and technology development in cotton harvesting robots; and (4) challenges in commercial deployment of agricultural robots, where challenges to commercializing and using these robots are reviewed. Conclusions are drawn about cotton harvesting robot research and the potential of multipurpose robotic operations in general. The development of multipurpose robots that can do multiple operations on different crops to increase the value of the robots is discussed. In each of the sections except the conclusion, the analysis is divided into four robotic system categories; mobility and steering, sensing and localization, path planning, and robotic manipulation.

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A robot platform for unmanned weeding in a paddy field using sensor fusion

Cited by 13 publications

References 11 publications

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Agricultural Robotics for Field Operations

An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting

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