Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.7
2.9
Journals
Robotics
Special Issues
Advances in Agriculture and Forest Robotics
share announcement

Advances in Agriculture and Forest Robotics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Agricultural and Field Robotics".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 86029

Special Issue Editors

Prof. Dr. Antonio Valente

E-Mail Website
Guest Editor
1. Habilitation at Engineering Department, UTAD—University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
2. INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
Interests: educational robotics; robotic competitions; robotics for agriculture; IoT; sensors; sensors for agriculture
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Paulo Moreira

E-Mail Website
Guest Editor
FEUP - Faculty of Engineering, University of Porto and INESC TEC - INESC Technology and Science, Porto, Portugal
Interests: control and automation; industrial manipulators and mobile robotics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. José Lima

E-Mail Website
Guest Editor
1. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Polytechnic Institute of Bragança, 5300-252 Bragança, Portugal
2. Centre for Robotics in Industry and Intelligent Systems (CRIIS), Institute for Systems and Computer Engineering, Technology and Science (INESC-TEC), 4200-465 Porto, Portugal
Interests: mobile robot localization; collaborative robots; IoT; path planning; simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Filipe Santos

E-Mail Website
Guest Editor
INESC TEC - INESC Technology and Science, Porto, Portugal
Interests: agricultural and forestry robots; IoT; sensors; sensors for agriculture

Special Issue Information

Dear Colleagues,

The growth of the world population, the increase in urbanization, and the significant change in consumption habits have led to a high demand for food by humans, which will increase dramatically in the coming decades—along with the impact of climate change (loss of biodiversity, deteriorating soil and water quality). On the other hand, there is also an increase in demand for forest products and a greater need to preserve forests.

Robotics research for use in agriculture and forestry has made great progress both in theoretical research and in practical applications.

This Special Issue is dedicated to new advances in robotics in agriculture and forestry. The objective is to publish the works developed in robotics with applications in the agricultural and forestry areas, in which automation and intelligence play important roles. The focus of this Special Issue is on the presentation of several theoretical and practical problems related to robotics, in addition to new discoveries, new ideas, and innovative improvements made in the field of robotics in agriculture and forestry.

Topics of interest include, but are not limited to the following:

  • Robots for pruning, thinning, harvesting, mowing, spraying, and weed removal
  • Robots for forest biomass harvesting
  • Robots for planting trees in forests
  • Fire-fighting robots
  • Aerial robots for forest monitoring
  • Aerial and ground robotic platforms for soil/crop monitoring, prediction, and decision making
  • Aerial robotics for environmental and agricultural applications
  • Fruit and flower detection and recognition
  • Approaches to cost-effective sensing for day/night continuous operation
  • Long-term autonomy and navigation in unstructured farming environments
  • Manipulators and platforms for soil preparation, seeding, crop protection, and harvesting
  • Adaptive sampling and informative data collection
  • Adaptive technologies that manage plants, soil, or animals according to as-sensed status
  • Theoretical and empirical decision-oriented data-analysis techniques including machine learning

Dr. Antonio Valente
Prof. António Paulo Moreira
Dr. José Lima
Dr. Filipe Santos
Guest Editors

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. Robotics is an international peer-reviewed open access monthly 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 1800 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

11 pages, 1491 KiB  
Article
A Case Study on Improving the Software Dependability of a ROS Path Planner for Steep Slope Vineyards
by Luís Carlos Santos, André Santos, Filipe Neves Santos and António Valente
Robotics 2021, 10(3), 103; https://doi.org/10.3390/robotics10030103 - 26 Aug 2021
Cited by 3 | Viewed by 3308
Abstract
Software for robotic systems is becoming progressively more complex despite the existence of established software ecosystems like ROS, as the problems we delegate to robots become more and more challenging. Ensuring that the software works as intended is a crucial (but not trivial) [...] Read more.
Software for robotic systems is becoming progressively more complex despite the existence of established software ecosystems like ROS, as the problems we delegate to robots become more and more challenging. Ensuring that the software works as intended is a crucial (but not trivial) task, although proper quality assurance processes are rarely seen in the open-source robotics community. This paper explains how we analyzed and improved a specialized path planner for steep-slope vineyards regarding its software dependability. The analysis revealed previously unknown bugs in the system, with a relatively low property specification effort. We argue that the benefits of similar quality assurance processes far outweigh the costs and should be more widespread in the robotics domain. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Figure 1

22 pages, 65733 KiB  
Article
A Study on the Feasibility of Robotic Harvesting for Chile Pepper
by Muhammad Umar Masood and Mahdi Haghshenas-Jaryani
Robotics 2021, 10(3), 94; https://doi.org/10.3390/robotics10030094 - 22 Jul 2021
Cited by 8 | Viewed by 7242
Abstract
This paper presents a study on the robotic harvesting of New Mexico type chile pepper, in a laboratory setting, using a five degrees of freedom (DoF) serial manipulator. The end-effector of the manipulator, a scissor-type cutting mechanism, was devised and experimentally tested in [...] Read more.
This paper presents a study on the robotic harvesting of New Mexico type chile pepper, in a laboratory setting, using a five degrees of freedom (DoF) serial manipulator. The end-effector of the manipulator, a scissor-type cutting mechanism, was devised and experimentally tested in a lab setup which cuts the chile stem to detach the fruit. Through a MATLAB™-based program, the location of the chile pepper is estimated in the robot’s reference frame, using Intel RealSense Depth Camera. The accuracy of the 3D location estimation system matches the maximum accuracy claimed by the manufacturer of the hardware, with a maximum error to be in Y-axis, which is 5.7 mm. The forward and inverse kinematics are developed, and the reachable and dexterous workspaces of the robot are studied. An application-based path planning algorithm is developed to minimize the travel for a specified harvesting task. The robotic harvesting system was able to cut the chile pepper from the plant based on 3D location estimated by MATLAB™ program. On the basis of harvesting operation, on 77 chile peppers, the following harvesting indicators were achieved: localization success rate of 37.7%, detachment success rate of 65.5%, harvest success rate of 24.7%, damage rate of 6.9%, and cycle time of 7 s. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Figure 1

26 pages, 3090 KiB  
Article
Prototype Development of Small Mobile Robots for Mallard Navigation in Paddy Fields: Toward Realizing Remote Farming
by Hirokazu Madokoro, Satoshi Yamamoto, Yo Nishimura, Stephanie Nix, Hanwool Woo and Kazuhito Sato
Robotics 2021, 10(2), 63; https://doi.org/10.3390/robotics10020063 - 27 Apr 2021
Cited by 12 | Viewed by 7129
Abstract
This study was conducted to develop robot prototypes of three models that navigate mallards to achieve high-efficiency rice-duck farming. We examined two robotics navigation approaches based on imprinting and feeding. As the first approach, we used imprinting applied to baby mallards. They exhibited [...] Read more.
This study was conducted to develop robot prototypes of three models that navigate mallards to achieve high-efficiency rice-duck farming. We examined two robotics navigation approaches based on imprinting and feeding. As the first approach, we used imprinting applied to baby mallards. They exhibited follow behavior to our first prototype after imprinting. Experimentally obtained observation results revealed the importance of providing imprinting immediately up to one week after hatching. As another approach, we used feed placed on the top of our second prototype. Experimentally obtained results showed that adult mallards exhibited wariness not only against the robot, but also against the feeder. After relieving wariness with provision of more than one week time to become accustomed, adult mallards ate feed in the box on the robot. However, they ran away immediately at a slight movement. Based on this confirmation, we developed the third prototype as an autonomous mobile robot aimed for mallard navigation in a paddy field. The body width is less than the length between rice stalks. After checking the waterproof capability of a body waterproof box, we conducted an indoor driving test for manual operation. Moreover, we conducted outdoor evaluation tests to assess running on an actual paddy field. We developed indoor and outdoor image datasets using an onboard monocular camera. For the outdoor image datasets, our segmentation method based on SegNet achieved semantic segmentation for three semantic categories. For the indoor image datasets, our prediction method based on CNN and LSTM achieved visual prediction for three motion categories. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Figure 1

22 pages, 28290 KiB  
Article
Occupancy Grid and Topological Maps Extraction from Satellite Images for Path Planning in Agricultural Robots
by Luís Carlos Santos, André Silva Aguiar, Filipe Neves Santos, António Valente and Marcelo Petry
Robotics 2020, 9(4), 77; https://doi.org/10.3390/robotics9040077 - 24 Sep 2020
Cited by 27 | Viewed by 6203
Abstract
Robotics will significantly impact large sectors of the economy with relatively low productivity, such as Agri-Food production. Deploying agricultural robots on the farm is still a challenging task. When it comes to localising the robot, there is a need for a preliminary map, [...] Read more.
Robotics will significantly impact large sectors of the economy with relatively low productivity, such as Agri-Food production. Deploying agricultural robots on the farm is still a challenging task. When it comes to localising the robot, there is a need for a preliminary map, which is obtained from a first robot visit to the farm. Mapping is a semi-autonomous task that requires a human operator to drive the robot throughout the environment using a control pad. Visual and geometric features are used by Simultaneous Localisation and Mapping (SLAM) Algorithms to model and recognise places, and track the robot’s motion. In agricultural fields, this represents a time-consuming operation. This work proposes a novel solution—called AgRoBPP-bridge—to autonomously extract Occupancy Grid and Topological maps from satellites images. These preliminary maps are used by the robot in its first visit, reducing the need of human intervention and making the path planning algorithms more efficient. AgRoBPP-bridge consists of two stages: vineyards row detection and topological map extraction. For vineyards row detection, we explored two approaches, one that is based on conventional machine learning technique, by considering Support Vector Machine with Local Binary Pattern-based features, and another one found in deep learning techniques (ResNET and DenseNET). From the vineyards row detection, we extracted an occupation grid map and, by considering advanced image processing techniques and Voronoi diagrams concept, we obtained a topological map. Our results demonstrated an overall accuracy higher than 85% for detecting vineyards and free paths for robot navigation. The Support Vector Machine (SVM)-based approach demonstrated the best performance in terms of precision and computational resources consumption. AgRoBPP-bridge shows to be a relevant contribution to simplify the deployment of robots in agriculture. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Figure 1

Review

Jump to: Research

20 pages, 46680 KiB  
Review
Advances in Forest Robotics: A State-of-the-Art Survey
by Luiz F. P. Oliveira, António P. Moreira and Manuel F. Silva
Robotics 2021, 10(2), 53; https://doi.org/10.3390/robotics10020053 - 24 Mar 2021
Cited by 49 | Viewed by 14883
Abstract
The development of robotic systems to operate in forest environments is of great relevance for the public and private sectors. In this sense, this article reviews several scientific papers, research projects and commercial products related to robotic applications for environmental preservation, monitoring, wildfire [...] Read more.
The development of robotic systems to operate in forest environments is of great relevance for the public and private sectors. In this sense, this article reviews several scientific papers, research projects and commercial products related to robotic applications for environmental preservation, monitoring, wildfire firefighting, inventory operations, planting, pruning and harvesting. After conducting critical analysis, the main characteristics observed were: (a) the locomotion system is directly affected by the type of environmental monitoring to be performed; (b) different reasons for pruning result in different locomotion and cutting systems; (c) each type of forest, in each season and each type of soil can directly interfere with the navigation technique used; and (d) the integration of the concept of swarm of robots with robots of different types of locomotion systems (land, air or sea) can compensate for the time of executing tasks in unstructured environments. Two major areas are proposed for future research works: Internet of Things (IoT)-based smart forest and navigation systems. It is expected that, with the various characteristics exposed in this paper, the current robotic forest systems will be improved, so that forest exploitation becomes more efficient and sustainable. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Graphical abstract

31 pages, 54526 KiB  
Review
Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead
by Luiz F. P. Oliveira, António P. Moreira and Manuel F. Silva
Robotics 2021, 10(2), 52; https://doi.org/10.3390/robotics10020052 - 24 Mar 2021
Cited by 211 | Viewed by 33292
Abstract
The constant advances in agricultural robotics aim to overcome the challenges imposed by population growth, accelerated urbanization, high competitiveness of high-quality products, environmental preservation and a lack of qualified labor. In this sense, this review paper surveys the main existing applications of agricultural [...] Read more.
The constant advances in agricultural robotics aim to overcome the challenges imposed by population growth, accelerated urbanization, high competitiveness of high-quality products, environmental preservation and a lack of qualified labor. In this sense, this review paper surveys the main existing applications of agricultural robotic systems for the execution of land preparation before planting, sowing, planting, plant treatment, harvesting, yield estimation and phenotyping. In general, all robots were evaluated according to the following criteria: its locomotion system, what is the final application, if it has sensors, robotic arm and/or computer vision algorithm, what is its development stage and which country and continent they belong. After evaluating all similar characteristics, to expose the research trends, common pitfalls and the characteristics that hinder commercial development, and discover which countries are investing into Research and Development (R&D) in these technologies for the future, four major areas that need future research work for enhancing the state of the art in smart agriculture were highlighted: locomotion systems, sensors, computer vision algorithms and communication technologies. The results of this research suggest that the investment in agricultural robotic systems allows to achieve short—harvest monitoring—and long-term objectives—yield estimation. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Graphical abstract

23 pages, 4993 KiB  
Review
Localization and Mapping for Robots in Agriculture and Forestry: A Survey
by André Silva Aguiar, Filipe Neves dos Santos, José Boaventura Cunha, Héber Sobreira and Armando Jorge Sousa
Robotics 2020, 9(4), 97; https://doi.org/10.3390/robotics9040097 - 21 Nov 2020
Cited by 89 | Viewed by 12018
Abstract
Research and development of autonomous mobile robotic solutions that can perform several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots are now used for a variety of tasks such as planting, harvesting, environmental monitoring, supply of water and nutrients, and others. [...] Read more.
Research and development of autonomous mobile robotic solutions that can perform several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots are now used for a variety of tasks such as planting, harvesting, environmental monitoring, supply of water and nutrients, and others. To do so, robots need to be able to perform online localization and, if desired, mapping. The most used approach for localization in agricultural applications is based in standalone Global Navigation Satellite System-based systems. However, in many agricultural and forest environments, satellite signals are unavailable or inaccurate, which leads to the need of advanced solutions independent from these signals. Approaches like simultaneous localization and mapping and visual odometry are the most promising solutions to increase localization reliability and availability. This work leads to the main conclusion that, few methods can achieve simultaneously the desired goals of scalability, availability, and accuracy, due to the challenges imposed by these harsh environments. In the near future, novel contributions to this field are expected that will help one to achieve the desired goals, with the development of more advanced techniques, based on 3D localization, and semantic and topological mapping. In this context, this work proposes an analysis of the current state-of-the-art of localization and mapping approaches in agriculture and forest environments. Additionally, an overview about the available datasets to develop and test these approaches is performed. Finally, a critical analysis of this research field is done, with the characterization of the literature using a variety of metrics. Full article
(This article belongs to the Special Issue Advances in Agriculture and Forest Robotics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop