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Robotics
Special Issues
Intelligent Technologies and Robotics
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Intelligent Technologies and Robotics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Intelligent Robots and Mechatronics".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 29542

Special Issue Editors

Dr. Filippo Sanfilippo

E-Mail Website
Guest Editor
Department of Engineering Sciences, University of Agder (UiA), Grimstad, Norway
Interests: collaborative robots; haptics; manipulators; digital twins; educational robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Gionata Salvietti

E-Mail Website
Guest Editor
Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy
Interests: robotic and human grasping; modular robot; assistive robotics; teleoperation; contact modelling; wearable haptics
Dr. Marco Aggravi

E-Mail Website
Guest Editor
CNRS, Univ Rennes, Inria, IRISA – Rennes, 35000 Rennes, France
Interests: human-robot interaction; robotics; haptics

Special Issue Information

Dear Colleagues,

Robotics is progressing at a much faster pace than ever before. This progress is synergistically stimulated by the cross-cutting, transformational effects of artificial intelligence (AI) and intelligent technologies. It is crucial to foster a greater awareness of this co-creation process and to give adequate consideration to societal needs, sustainability perspectives, and accountability.

This Special Issue is open to interdisciplinary approaches, and it aims at exhibiting the latest research achievements, findings, and ideas in the areas of “Intelligent Technologies and Robotics”. The issue will contain revised and substantially extended versions of selected papers that were presented at the 4th International Conference on Intelligent Technologies and Applications (INTAP'21), but we also strongly encourage researchers unable to participate in the conference to submit articles for this call.

Papers are welcomed on topics that are related to intelligent technologies within the aspects of theory, design, practice, and applications for robotics, including, but not limited to:

  • Machine and mechanism design
  • Industrial IT
  • Intelligent monitoring
  • Robotics and vision
  • Collaborative robots
  • Urban ocean technology
  • Haptics
  • Theoretical and computational kinematics/dynamics
  • Dynamics of machinery and multibody systems
  • Control issues
  • Machine intelligence
  • Intelligent applications
  • Educational robotics

Dr. Filippo Sanfilippo
Dr. Gionata Salvietti
Dr. Marco Aggravi
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.

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • 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 policies can be found here.

Published Papers (4 papers)

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Research

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24 pages, 8017 KiB  
Article
A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm
by Hua Minh Tuan, Filippo Sanfilippo and Nguyen Vinh Hao
Robotics 2022, 11(2), 47; https://doi.org/10.3390/robotics11020047 - 5 Apr 2022
Cited by 18 | Viewed by 5230
Abstract
Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of [...] Read more.
Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s). Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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17 pages, 5339 KiB  
Article
Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators
by Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo
Robotics 2022, 11(2), 43; https://doi.org/10.3390/robotics11020043 - 2 Apr 2022
Cited by 7 | Viewed by 4146
Abstract
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the [...] Read more.
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees of Freedom (DOF) manipulator on the Robot Operating System (ROS). The dataset created from the simulation is divided 65–35 for training–testing of the proposed model. The metrics used for model validation include spread value, cost and runtime for the training dataset, and Mean Relative Error, Normal Mean Square Error, and Mean Absolute Error for the testing dataset. A comparative analysis of the CSOA-RBFNN model is performed with an artificial neural network, support vector regression model, and with with other meta-heuristic RBFNN models, i.e., PSO-RBFNN and GWO-RBFNN, that show the effectiveness and superiority of the proposed technique. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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14 pages, 3677 KiB  
Article
The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot
by Askan Duivon, Pino Kirsch, Boris Mauboussin, Gabriel Mougard, Jakub Woszczyk and Filippo Sanfilippo
Robotics 2022, 11(2), 42; https://doi.org/10.3390/robotics11020042 - 1 Apr 2022
Cited by 12 | Viewed by 4266
Abstract
The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from [...] Read more.
The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from a control standpoint, the accurate identification of push-points and reliable determination of feasible contact reaction forces are required. This is difficult to achieve with rigidly actuated robots because of the lack of compliance. As a possible solution to this challenge, our research group recently presented Serpens, a low-cost, open-source, and highly compliant multi-purpose modular snake robot with a series elastic actuator (SEA). In this paper, we propose a new prototyping iteration for our snake robot to achieve a more dependable design. The following three contributions are outlined in this work as a whole: the remodelling of the elastic joint with the addition of a damper element; a refreshed design for the screw-less assembly mechanism that can now withstand higher transverse forces; the re-design of the joint module with an improved reorganisation of the internal hardware components to facilitate heat dissipation and to accommodate a larger battery with easier access. The Robot Operating System (ROS) serves as the foundation for the software architecture. The possibility of applying machine learning approaches is considered. The results of preliminary simulations are provided. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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Review

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20 pages, 1631 KiB  
Review
A Perspective Review on Integrating VR/AR with Haptics into STEM Education for Multi-Sensory Learning
by Filippo Sanfilippo, Tomas Blazauskas, Gionata Salvietti, Isabel Ramos, Silviu Vert, Jaziar Radianti, Tim A. Majchrzak and Daniel Oliveira
Robotics 2022, 11(2), 41; https://doi.org/10.3390/robotics11020041 - 31 Mar 2022
Cited by 58 | Viewed by 14625
Abstract
As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and [...] Read more.
As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and provide possibilities for remote learning. A variety of educational programs, platforms, and technologies are now accessible to support student learning; while these tools are important for society, they are primarily concerned with the dissemination of theoretical material. There is a lack of support for hands-on laboratory work and practical experience. This is particularly important for all disciplines related to science, technology, engineering, and mathematics (STEM), where labs and pedagogical assets must be continuously enhanced in order to provide effective study programs. In this study, we describe a unique perspective to achieving multi-sensory learning through the integration of virtual and augmented reality (VR/AR) with haptic wearables in STEM education. We address the implications of a novel viewpoint on established pedagogical notions. We want to encourage worldwide efforts to make fully immersive, open, and remote laboratory learning a reality. Full article
(This article belongs to the Special Issue Intelligent Technologies and Robotics)
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