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Machines
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New Trends in Robotics, Automation and Mechatronics
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New Trends in Robotics, Automation and Mechatronics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 19346

Special Issue Editor

Dr. Bao Kha Nguyen

E-Mail Website
Guest Editor
Department of Engineering and Design, University of Sussex, Brighton BN1 9QT, UK
Interests: control systems; industrial automation; mechatronics; robotics; control theory; smart sensors and actuators; real-time control systems for industrial and agricultural applications

Special Issue Information

Dear Colleagues,

Robotics, mechatronics and automation systems are always evolving, with new innovations transforming different industrial, agricultural, manufacturing, energy and healthcare systems. There has been an increase in the demand for these systems across different sectors in the post-pandemic era. The aim of this Special Issue is to provide new, up-to-date research trends in robotics, automation and mechatronics with contributions from researchers worldwide. This issue presents new research results and developments in the multidisciplinary field of robotics, mechatronics and automation. We welcome original theoretical and applied research and review papers that cover these related topics.

  • Applications of automation
  • Systems and control engineering
  • Electronic engineering
  • Mechanical engineering
  • Computer engineering
  • Mechatronics
  • Robotics
  • Human–machine interfaces
  • Machine vision

Dr. Bao Kha Nguyen
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. Machines 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 2400 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
  • mechatronics
  • control systems
  • control theory
  • control algorithms
  • artificial intelligence
  • machine learning
  • vision systems
  • image processing
  • precision farming
  • industrial robots
  • industrial automation
  • agricultural robots
  • medical robots
  • human–robot interactions
  • modelling
  • simulation
  • exoskeletons and prostheses
  • drones
  • UGVs
  • UAVs
  • virtual reality
  • industry 4.0 and 5.0

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Published Papers (10 papers)

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Research

Jump to: Review

22 pages, 25637 KiB  
Article
Low-Cost Real-Time Localisation for Agricultural Robots in Unstructured Farm Environments
by Chongxiao Liu and Bao Kha Nguyen
Machines 2024, 12(9), 612; https://doi.org/10.3390/machines12090612 - 2 Sep 2024
Cited by 1 | Viewed by 1016
Abstract
Agricultural robots have demonstrated significant potential in enhancing farm operational efficiency and reducing manual labour. However, unstructured and complex farm environments present challenges to the precise localisation and navigation of robots in real time. Furthermore, the high costs of navigation systems in agricultural [...] Read more.
Agricultural robots have demonstrated significant potential in enhancing farm operational efficiency and reducing manual labour. However, unstructured and complex farm environments present challenges to the precise localisation and navigation of robots in real time. Furthermore, the high costs of navigation systems in agricultural robots hinder their widespread adoption in cost-sensitive agricultural sectors. This study compared two localisation methods that use the Error State Kalman Filter (ESKF) to integrate data from wheel odometry, a low-cost inertial measurement unit (IMU), a low-cost real-time kinematic global navigation satellite system (RTK-GNSS) and the LiDAR-Inertial Odometry via Smoothing and Mapping (LIO-SAM) algorithm using a low-cost IMU and RoboSense 16-channel LiDAR sensor. These two methods were tested on unstructured farm environments for the first time in this study. Experiment results show that the ESKF sensor fusion method without a LiDAR sensor could save 36% of the cost compared to the method that used the LIO-SAM algorithm while maintaining high accuracy for farming applications. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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17 pages, 6264 KiB  
Article
ROMI: Design and Experimental Evaluation of a Linear Delta Robotic System for High-Precision Applications
by Xiaoyu Huang, Elizabeth Rendon-Morales and Rodrigo Aviles-Espinosa
Machines 2023, 11(12), 1072; https://doi.org/10.3390/machines11121072 - 6 Dec 2023
Cited by 1 | Viewed by 1844
Abstract
In this paper, the design and experimental evaluation of a parallel robotic system based on a linear delta geometry is presented. The design considers the requirements for high-precision applications including workspace, motion resolution, and payload. The entire design process includes robot kinematics, control, [...] Read more.
In this paper, the design and experimental evaluation of a parallel robotic system based on a linear delta geometry is presented. The design considers the requirements for high-precision applications including workspace, motion resolution, and payload. The entire design process includes robot kinematics, control, and optimization, resulting in the demonstration of a working device. The robot structure offers a versatile and simplified design when compared with state-of-the-art devices being able to be adapted to perform different tasks while keeping the advantages of high precision with reduced complexity. The presented robot prototype was constructed and evaluated experimentally through three proof-of-concept experiments mimicking tasks requiring high motion precision such as microsurgery, semiconductor testing, and optical device alignment. The obtained results in the three experimental scenarios validate that the here-proposed design can achieve an average motion precision of ~3.3 ± 0.3 μm with varying load conditions, thus confirming its potential to be used for high-precision tasks in industrial and medical settings. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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26 pages, 5610 KiB  
Article
5G on the Farm: Evaluating Wireless Network Capabilities and Needs for Agricultural Robotics
by Tsvetan Zhivkov, Elizabeth I. Sklar, Duncan Botting and Simon Pearson
Machines 2023, 11(12), 1064; https://doi.org/10.3390/machines11121064 - 30 Nov 2023
Cited by 3 | Viewed by 1915
Abstract
Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in [...] Read more.
Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in industry settings, moving from controlled labs and experimental test facilities to real-world environments. Such technologies require sufficient network infrastructure to support in-field operations; thus, there is increased urgency to establish reliable, high-speed wireless communication networking solutions that enable deployment of autonomous agri-robots. The work presented here includes two contributions at the intersection of network infrastructure and in-field agricultural robotics. First, the physical performance of a private 5G-SA system in an agri-robotics application is evaluated and in-field experimental results are presented. These results are compared (using the same experimental setup) against public 4G and private WiFi6 (a newly emerging wireless communication standard). Second, a simulated experiment was performed to assess the “real-time” operational delay in critical tasks that may require quick turnaround between in-field robot and off-board processing. The results demonstrate that public 4G cannot be used in the agricultural domain for applications that require high throughput and reliable communication; that private 5G-SA greatly outperforms public 4G in all performance metrics (as expected); and that private WiFi6, though limited in range, is a fast and very reliable alternative in specific settings. While a single wireless solution does not currently exist for the agricultural domain, multiple technologies can be combined in a hybrid solution that meets the communications requirements. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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22 pages, 2908 KiB  
Article
G-DMD: A Gated Recurrent Unit-Based Digital Elevation Model for Crop Height Measurement from Multispectral Drone Images
by Jinjin Wang, Nobuyuki Oishi, Phil Birch and Bao Kha Nguyen
Machines 2023, 11(12), 1049; https://doi.org/10.3390/machines11121049 - 25 Nov 2023
Viewed by 1285
Abstract
Crop height is a vital indicator of growth conditions. Traditional drone image-based crop height measurement methods primarily rely on calculating the difference between the Digital Elevation Model (DEM) and the Digital Terrain Model (DTM). The calculation often needs more ground information, which remains [...] Read more.
Crop height is a vital indicator of growth conditions. Traditional drone image-based crop height measurement methods primarily rely on calculating the difference between the Digital Elevation Model (DEM) and the Digital Terrain Model (DTM). The calculation often needs more ground information, which remains labour-intensive and time-consuming. Moreover, the variations of terrains can further compromise the reliability of these ground models. In response to these challenges, we introduce G-DMD, a novel method based on Gated Recurrent Units (GRUs) using DEM and multispectral drone images to calculate the crop height. Our method enables the model to recognize the relation between crop height, elevation, and growth stages, eliminating reliance on DTM and thereby mitigating the effects of varied terrains. We also introduce a data preparation process to handle the unique DEM and multispectral image. Upon evaluation using a cotton dataset, our G-DMD method demonstrates a notable increase in accuracy for both maximum and average cotton height measurements, achieving a 34% and 72% reduction in Root Mean Square Error (RMSE) when compared with the traditional method. Compared to other combinations of model inputs, using DEM and multispectral drone images together as inputs results in the lowest error for estimating maximum cotton height. This approach demonstrates the potential of integrating deep learning techniques with drone-based remote sensing to achieve a more accurate, labour-efficient, and streamlined crop height assessment across varied terrains. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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21 pages, 11569 KiB  
Article
A Novel Fully Automatic Concept to Produce First Subset of Bowden Cables, Improving Productivity, Flexibility, and Safety
by Eduardo Eiras, Francisco J. G. Silva, Raul D. S. G. Campilho, Rita C. M. Sales-Contini, André F. V. Pedroso and Naiara P. V. Sebbe
Machines 2023, 11(11), 992; https://doi.org/10.3390/machines11110992 - 26 Oct 2023
Viewed by 1530
Abstract
With a view to maintaining the competitiveness required by the market, the automotive industry strongly encourages its suppliers to develop new production methods and technologies capable of reducing the costs of produced products, ensuring the necessary quality, and increasing flexibility, with a view [...] Read more.
With a view to maintaining the competitiveness required by the market, the automotive industry strongly encourages its suppliers to develop new production methods and technologies capable of reducing the costs of produced products, ensuring the necessary quality, and increasing flexibility, with a view to responding more easily to the customization of the products that the market increasingly demands. The main goal of this work was to increase the flexibility and productivity of equipment capable of producing the first subset that constitutes the product commonly known as the Bowden cable. To this end, the design science research methodology was used, which was understood as the most effective in describing scientific work related to the improvement of existing systems. Bowden cables are cables that activate various devices in the car, such as opening doors, moving window glasses, and adjusting some car seats, among others. The work consisted of integrating several operations usually carried out for the manufacture of the referred subset, reducing logistics operations and manual work, increasing operator safety, and increasing the production rate and flexibility of the equipment, by reducing the setup time. For this purpose, new mechanical concepts were developed, and automation was applied, which resulted in a completely new concept, able to fulfill all the objectives initially set. It should be noted here that the new equipment allowed a production rate of 1140 p/h, when the initial objective was 1100 p/h; it requires an investment of only around EUR 55,000 (easy return on investment), occupies only 11.6 m2, and has reinforced safety systems to avoid workers’ injuries, an aspect that is very important in this type of equipment, where operators deal with cutting systems and high temperatures. The dissemination of this concept could help other researchers to easily find solutions to certain problems that they face in the development of modern equipment. The main contributions of this paper are the novel concepts created to overcome some process difficulties, which can be used for a wide range of other processing situations with similar difficulties. The solutions proposed allow a decrease in the cycle time, present high flexibility, save workshop space, and are affordable in terms of global cost. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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16 pages, 5763 KiB  
Article
Grasping Pose Estimation for Robots Based on Convolutional Neural Networks
by Tianjiao Zheng, Chengzhi Wang, Yanduo Wan, Sikai Zhao, Jie Zhao, Debin Shan and Yanhe Zhu
Machines 2023, 11(10), 974; https://doi.org/10.3390/machines11100974 - 20 Oct 2023
Cited by 2 | Viewed by 2465
Abstract
Robots gradually have the ability to plan grasping actions in unknown scenes by learning the manipulation of typical scenes. The grasping pose estimation method, as a kind of end-to-end method, has rapidly developed in recent years because of its good generalization. In this [...] Read more.
Robots gradually have the ability to plan grasping actions in unknown scenes by learning the manipulation of typical scenes. The grasping pose estimation method, as a kind of end-to-end method, has rapidly developed in recent years because of its good generalization. In this paper, we present a grasping pose estimation method for robots based on convolutional neural networks. In this method, a convolutional neural network model was employed, which can output the grasping success rate, approach angle, and gripper opening width for the input voxel. The grasping dataset was produced, and the model was trained in the physical simulator. A position optimization of the robotic grasping was proposed according to the distribution of the object centroid to improve the grasping success rate. An experimental platform for robot grasping was established, and 11 common everyday objects were selected for the experiments. Grasping experiments involving the eleven objects individually, multiple objects, as well as a dark environment without illumination, were performed. The results show that the method has the adaptability to grasp different geometric objects, including irregular shapes, and it is not influenced by lighting conditions. The total grasping success rate was 88.2% for the individual objects and 81.1% for the cluttered scene. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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14 pages, 3300 KiB  
Article
Multivariable Linear Position Control Based on Active Disturbance Rejection for Two Linear Slides Coupled to a Mass
by Fabio Abel Gómez Becerra, Jonathan Villanueva Tavira, Héctor Miguel Buenabad Arias, Andrés Blanco Ortega, Estela Sarmiento Bustos, Manuela Calixto Rodríguez and Jorge Salvador Valdez Martinez
Machines 2023, 11(9), 889; https://doi.org/10.3390/machines11090889 - 5 Sep 2023
Cited by 1 | Viewed by 1052
Abstract
Active Disturbance Rejection Control (ADRC) is a promising approach that has emerged to deal with uncertainties, which has received many practical applications in motion controls. This paper presents a multivariable controller for active disturbance rejection (ADR) based on an extended state linear observer [...] Read more.
Active Disturbance Rejection Control (ADRC) is a promising approach that has emerged to deal with uncertainties, which has received many practical applications in motion controls. This paper presents a multivariable controller for active disturbance rejection (ADR) based on an extended state linear observer for tracking the linear position trajectory of a mass moved by two linear slides, each one driven by a DC motor. The linear extended state observer is used to estimate the endogenous and exogenous disturbances of the system, which are assumed to be unknown, but bounded. Therefore, the feedback system prevents each actuator from operating at different forward speeds, and thus a synchronization between the two actuators is achieved by moving the common mass smoothly. The simulation and the experimental results show the effectiveness and robustness of the controller proposal when moving the mass with both actuators. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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23 pages, 3129 KiB  
Article
Fast Grasping Technique for Differentiated Mobile Phone Frame Based on Visual Guidance
by Rongli Zhao, Zeren Bao, Wanyu Xiao, Shangwen Zou, Guangxin Zou, Yuan Xie and Jiewu Leng
Machines 2023, 11(7), 689; https://doi.org/10.3390/machines11070689 - 30 Jun 2023
Cited by 1 | Viewed by 1610
Abstract
With the increasing automation of mobile phone assembly, industrial robots are gradually being used in production lines for loading and unloading operations. At present, industrial robots are mainly used in online teaching mode, in which the robot’s movement and path are set by [...] Read more.
With the increasing automation of mobile phone assembly, industrial robots are gradually being used in production lines for loading and unloading operations. At present, industrial robots are mainly used in online teaching mode, in which the robot’s movement and path are set by teaching in advance and then repeat the point-to-point operation. This mode of operation is less flexible and requires high professionalism in teaching and offline programming. When positioning and grasping different materials, the adjustment time is long, which affects the efficiency of production changeover. To solve the problem of poor adaptability of loading robots to differentiated products in mobile phone automatic assembly lines, it is necessary to quickly adjust the positioning and grasping of different models of mobile phone middle frames. Therefore, this paper proposes a highly adaptive grasping and positioning method for vision-guided right-angle robots. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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Review

Jump to: Research

20 pages, 409 KiB  
Review
Heuristics and Rescheduling in Prioritised Multi-Robot Path Planning: A Literature Review
by James R. Heselden and Gautham P. Das
Machines 2023, 11(11), 1033; https://doi.org/10.3390/machines11111033 - 20 Nov 2023
Cited by 1 | Viewed by 1956
Abstract
The benefits of multi-robot systems are substantial, bringing gains in efficiency, quality, and cost, and they are useful in a wide range of environments from warehouse automation, to agriculture and even extend in part to entertainment. In multi-robot system research, the main focus [...] Read more.
The benefits of multi-robot systems are substantial, bringing gains in efficiency, quality, and cost, and they are useful in a wide range of environments from warehouse automation, to agriculture and even extend in part to entertainment. In multi-robot system research, the main focus is on ensuring efficient coordination in the operation of the robots, both in task allocation and navigation. However, much of this research seldom strays from the theoretical bounds; there are many reasons for this, with the most-prominent and -impactful being resource limitations. This is especially true for research in areas such as multi-robot path planning (MRPP) and navigation coordination. This is a large issue in practice as many approaches are not designed with meaningful real-world implications in mind and are not scalable to large multi-robot systems. This survey aimed to look into the coordination and path-planning issues and challenges faced when working with multi-robot systems, especially those using a prioritised planning approach, and identify key areas that are not well-explored and the scope of applying existing MRPP approaches to real-world settings. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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27 pages, 1001 KiB  
Review
Deformable Object Manipulation in Caregiving Scenarios: A Review
by Liman Wang and Jihong Zhu
Machines 2023, 11(11), 1013; https://doi.org/10.3390/machines11111013 - 7 Nov 2023
Viewed by 2754
Abstract
This paper reviews the robotic manipulation of deformable objects in caregiving scenarios. Deformable objects like clothing, food, and medical supplies are ubiquitous in care tasks, yet pose modeling, control, and sensing challenges. This paper categorises caregiving deformable objects and analyses their distinct properties [...] Read more.
This paper reviews the robotic manipulation of deformable objects in caregiving scenarios. Deformable objects like clothing, food, and medical supplies are ubiquitous in care tasks, yet pose modeling, control, and sensing challenges. This paper categorises caregiving deformable objects and analyses their distinct properties influencing manipulation. Key sections examine progress in simulation, perception, planning, control, and system designs for deformable object manipulation, along with end-to-end deep learning’s potential. Hybrid analytical data-driven modeling shows promise. While laboratory successes have been achieved, real-world caregiving applications lag behind. Enhancing safety, speed, generalisation, and human compatibility is crucial for adoption. The review synthesises critical technologies, capabilities, and limitations, while also pointing to open challenges in deformable object manipulation for robotic caregiving. It provides a comprehensive reference for researchers tackling this socially valuable domain. In conclusion, multi-disciplinary innovations combining analytical and data-driven methods are needed to advance real-world robot performance and safety in deformable object manipulation for patient care. Full article
(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics)
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