Robotics and Automation Engineering in Agriculture

A special issue of AgriEngineering (ISSN 2624-7402).

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 33226

Special Issue Editor


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Guest Editor
Cotton Production and Processing Research Unit, United States Department of Agriculture, Agricultural Research Services, Lubbock, TX 79403, USA
Interests: instrumentation and sensor development; robotics; microwave sensing; machine-vision; artificial-intelligence
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Special Issue Information

Dear Colleagues,

With the advent of the recent leaps in artificial intelligence; we are on the verge of a new explosion of autonomous systems and machines.  By leveraging open-source efforts and keeping close working ties to research groups working in similar areas; the advancements towards the goal of obtaining low-cost fully autonomous systems suitable for use in agriculture will advance rapidly.  As the world struggles to increase food production by 60% in the next decade, while at the same time losing key labor pools, it is imperative that the advances take place on an accelerated time-line.  In order to exploit the new-found capabilities brought by recent advances in artificial intelligence, authoritative studies are need to published in widely distributed research journals.  Further by leveraging open-source, which this journal is accelerating access to, our objectives are to lose the old paradigm by which competing research groups have to re-invent the technology developed from closed source parallel research groups and instead enable each parallel research group to help each other accelerate towards the common goal by removing these barriers by leveraging a common open-source code and system design base.  With open-source efforts, and close cooperation between parallel efforts, no-one should have to re-write code that other groups have already developed or redesign mechanical or electrical systems that were developed by other groups.  This sharing of resources should rapidly accelerate the pace of progress and help us to achieve the transition from manned equipment to that of low cost fully automated working farms and food production operations.  Your efforts towards these goals will be invaluable and greatly needed if we are to hope to feed the world’s population over next 10-20 years.

This Special Issue is aimed at bringing together recent developments related to robotics and automation with respect to their potential or proven capabilities when used in agricultural applications. Contributions are expected to deal with, but are not limited to, the following areas:

  • Robotics
  • Machine-Vision
  • Computer-Vision
  • Stereo-Vision
  • Automation
  • CNC
  • Computer Numerical Control
  • Artificial Intelligence
  • AI
  • DNN
  • Deep Neural Networks
  • Convolutional Networks
  • Tensor-Flow
  • YOLO
  • Caffe
  • Dark-Flow
  • Dark-Net
  • Radar
  • Lidar
  • Sensors
  • Instrumentation
  • Acoustics
  • Spectroscopy
  • Soil, vegetation, air and water sensors
  • Livestock sensors
  • On the go sensing
  • Non-destructive sensing
  • Proximal and remote sensing
  • Multispectral and Hyperspectral sensors and vegetation indexes
  • Fluorescence and thermal imaging
  • Sensors for determination of crop health status
  • Sensors for determination of animal health status
  • Real-time monitoring of animal bio-responses
  • Sensors for automated animal management
  • Integration of sensors in agricultural machines: automation and controls
  • Yield monitoring
  • Monitoring of different growth stages of crops and phenotyping
  • Early detection of diseases and pests
  • Multi-sensor systems, sensor fusion, data-fusion
  • Detection and identification of crops and weeds
  • Sensors for detection of fruits and quality determination
  • Sensors for positioning, navigation, and obstacle detection
  • Advanced characterization techniques
  • Sensor networks and IOT in agriculture and livestock sectors
  • Sensors solution for precision agriculture and precision livestock farming

Dr. Mathew G. Pelletier
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Robotics
  • Automation
  • Radar
  • Lidar
  • Machine-Learning
  • Machine-Vision
  • Artificial Intelligence
  • Deep Neural Networks
  • Convolutional Networks

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Published Papers (6 papers)

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Research

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12 pages, 6546 KiB  
Article
A Small Versatile Electrical Robot for Autonomous Spraying in Agriculture
by Luciano Cantelli, Filippo Bonaccorso, Domenico Longo, Carmelo Donato Melita, Giampaolo Schillaci and Giovanni Muscato
AgriEngineering 2019, 1(3), 391-402; https://doi.org/10.3390/agriengineering1030029 - 6 Aug 2019
Cited by 76 | Viewed by 12605
Abstract
Boosting innovation and research in the agricultural sector is crucial if farmers are asked to produce more with less. Precision agriculture offers different solutions to assist farmers in improving efficiency and reducing labor costs while respecting the legal requirements. Precision spraying enables the [...] Read more.
Boosting innovation and research in the agricultural sector is crucial if farmers are asked to produce more with less. Precision agriculture offers different solutions to assist farmers in improving efficiency and reducing labor costs while respecting the legal requirements. Precision spraying enables the treatment of only the plants that require it, with the right amount of products. Our research group has developed a solution based on a reconfigurable vehicle with a high degree of automation for the distribution of plant protection products in vineyards and greenhouses. The synergy between the vehicle and the spraying management system we developed is an innovative solution with high technological content, and attempts to account for the current European and global directives in the field of agricultural techniques. The objectives of our system are the development of an autonomous vehicle and a spraying management system that allows safe and accurate autonomous spraying operations. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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13 pages, 2877 KiB  
Article
Effect of Soil Moisture Content and End-Effector Speed on Pick-up Force and Lump Damage for Seedling Transplanting
by Sami Mohamed and Jizhan Liu
AgriEngineering 2019, 1(3), 343-355; https://doi.org/10.3390/agriengineering1030026 - 22 Jul 2019
Cited by 6 | Viewed by 3749
Abstract
Efficient transplanting has been identified as one of the essential steps towards achieving an increased yield in the farm. However, many factors are affecting these processes such as soil moisture content and the speed of pickup. This study was carried out to investigate [...] Read more.
Efficient transplanting has been identified as one of the essential steps towards achieving an increased yield in the farm. However, many factors are affecting these processes such as soil moisture content and the speed of pickup. This study was carried out to investigate the effect of different soil moisture content and pickup speeds on pickup force, balance, resistance, and lump damage during transplanting of seedlings. The results showed that penetration resistance was inversely proportional to the speed and soil moisture content. The highest penetration resistance (38 N) values were recorded under the lowest speed (0.5 mm/s) at the low moisture content; whereas, the lowest penetration resistance was obtained at highest speed (10 mm/s) under high moisture content. The highest pick-up force resistance values were recorded under the lowest speed (0.5 mm/s) at low moisture content than the lowest pick-up force resistance of 1.4 N at (10 mm/s) under the high moisture content. On the other hand, an increase of pick-up force led to a decrease in the pick-up force resistance. The pick-up damage and the pick-up speed are directly proportional—nevertheless, the former increased with a decreasing soil moisture content. The highest pick-up damage values (82%) were observed under the top-most speed (10 mm/s) at high moisture content. It can be concluded that for successful auto-transplanting of seedling the soil condition, the force applied and speed should be taken into consideration. This work will implement an effective seedling-picking performance and basis for the optimal design of end-effectors. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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11 pages, 3727 KiB  
Technical Note
Thermal Performance of Double-Sided Metal Core PCBs
by Mathew G. Pelletier, Stone C. Preston, Jim A. Cook, Kevin D. Tran, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 539-549; https://doi.org/10.3390/agriengineering1040039 - 13 Nov 2019
Cited by 1 | Viewed by 3896
Abstract
Thermal management in printed circuit boards is becoming increasingly more important as the use of LEDs is now widespread across all industries. Due to availability of the preferred electronic LED current drivers and system constraints for a machine-vision application, the design dictated the [...] Read more.
Thermal management in printed circuit boards is becoming increasingly more important as the use of LEDs is now widespread across all industries. Due to availability of the preferred electronic LED current drivers and system constraints for a machine-vision application, the design dictated the need for a double-sided metal core printed circuit board (MCPCB). However, design information for this relatively new MCPCB offering is sparse to non-existent. To fill-in this missing information in the literature, experiments were conducted where LEDs were arranged on a double-sided metal core printed circuit board (MCPCB), and their impact on the board temperature distribution was tested in a static fan-less configuration where the first condition was at room temperature, 23 °C, and the second configuration was for a heated environment, 40 °C. Two MCPCB orientations were tested (vertical and horizontal). Additionally, several LED arrangements on the MCPCB were configured, and temperatures were measured using a thermocouple as well as with a deep-infrared thermal imaging camera. Maximum temperatures were found to be 65.3 °C for the room temperature tests and 96.4 °C for the heated tests with high temperatures found in near proximity to the heat sources (LEDs), indicating less than ideal heat-conduction/dissipation by the MCPCB. The results indicate that the double-sided MCPCB topology is not efficient for high thermally loaded systems, especially when the target is a fan-less system. The results of testing indicate that for fan-less systems requiring high-performance heat-transfer, these new MCPCB are not a suitable design alternative, and instead, designers should stick with the more traditional single-sided metal-back PCB. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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16 pages, 11608 KiB  
Technical Note
Electronic Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 523-538; https://doi.org/10.3390/agriengineering1040038 - 22 Oct 2019
Cited by 5 | Viewed by 4330
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the electronic system design for a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed the basket time to settle, then weighed the contents of the basket. The software running the system was split into two parts that were run on an embedded low-level micro-controller and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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12 pages, 2531 KiB  
Technical Note
Man-Machine-Interface Software Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 511-522; https://doi.org/10.3390/agriengineering1040037 - 21 Oct 2019
Cited by 6 | Viewed by 3802
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the man-machine-interface software system design portion of a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed basket time to settle, then weighed the contents of the basket. The software running the system was split into two parts that were run on an embedded low-level micro-controller, and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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11 pages, 3800 KiB  
Technical Note
Embedded Micro-Controller Software Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 485-495; https://doi.org/10.3390/agriengineering1040035 - 10 Oct 2019
Cited by 7 | Viewed by 3477
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the embedded micro-controller software system design portion of a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed the basket time to settle, and then weighed the contents of the basket. The software running the system was split into two parts, which were run on an embedded low-level micro-controller and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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