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Versatile Intelligent Portable Interfaces for Human-Robot Interaction Systems

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4568

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Special Issue Editors

Prof. Dr. Luige Vladareanu

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Guest Editor

Institute of Solid Mechanics of the Romanian Academy, 010141 Bucharest, Romania
Interests: real time control systems; H2R; neutrosophical logic and H2R; H2R and extenics theory; M2M; AI; robotics; mechatronics; CPS; IoT; dynamic systems and control
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Florentin Smarandache

E-Mail Website
Guest Editor

Department of Mathematics, University of New Mexico, Gallup, NM 87301, USA
Interests: neutrosophic probability; neutrosophic statistics; neutrosophic algebraic structures; plithogenic set; unmatter; superluminal physics; paradoxism; quantum paradoxes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advanced intelligent control is a rapidly developing, complex and challenging field in an interdisciplinary field such as robotics, with great practical importance and potential. This has necessitated that authors advance science and technology and provide theoretical and practical considerations of intelligent control techniques and their application using intelligent sensors integrated through versatile intelligent portable platforms for human–robot interaction systems.

Advanced intelligent control is an inter-disciplinary field, which combines and extends theories and methods from control theory, computer science, and operations research areas, with the aim of developing using VIP interfaces that are highly adaptable to human–robot interaction.

Advances in sensors, actuators, computation technology and communication networks help provide the necessary tools for the implementation of intelligent control hardware.

Practical applications using intelligent sensors for this control method, which have emerged from artificial intelligence and computer controlled systems as an interdisciplinary field, are aimed toward a variety of relevant scientific research fields on extensions of traditional techniques through Neutrosophic logic, Extenics control, artificial intelligence in general and machine learning—including deep learning, bio-inspired algorithms, Petri nets, recurrent neural networks, neuro-fuzzy control, Bayesian control, genetic control, intelligent agents (cognitive/conscious control).

The scope of this Special Issue is to present and communicate new trends in the design, control and applications of real time control of intelligent sensors systems using advanced intelligent control methods and techniques.

We encourage submissions using innovative human–robot (H2R) interaction systems, machine-to-machine (M2M) interfaces, Neutrosophic logic, Extenics control applied on H2R, multi-sensor fusion techniques integrated through versatile intelligent portable (VIP) platforms, combined with computer vision, virtual and augmented reality (VR&AR), intelligent communication including remote control, adaptive sensor networks, intelligent decision support systems (IDSS) including remote sensing and their integration with DSS, GA-based DSS, fuzzy sets DSS, rough sets-based DSS, intelligent agent-assisted DSS, process mining integration to decision support, adaptive DSS, computer-vision-based DSS and sensory and robotic DSS.

We also welcome the utilization of new technologies, relevant for human–robot interaction, using advanced intelligent control through versatile intelligent portable platforms for enhanced IoT technologies and applications in the 5G densification era, bio-inspired techniques in future manufacturing enterprise control, cyber–physical systems approach to cognitive enterprise, developing the IT Industry 4.0 concept, industrial systems in the digital age, cloud computing, robotics and automation with applications such as human aid mechatronics, moving in unstructured and uneven environments for military applications, rescue robots, firefighting robots, rehabilitation robots, robot-assisted surgery and domestic robots.

We welcome submissions of original research papers and review articles that report recent advancements in intelligent control using intelligent sensors for human–robot interaction.

Prof. Dr. Luige Vladareanu
Prof. Dr. Florentin Smarandache
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

versatile intelligent portable platforms
human-to-robot (H2R) interaction systems
neutrosophical logic and H2R
H2R and extenics theory
machine-to-machine (M2M) interfaces
robot control
intelligent control
artificial intelligence
intelligent agents
intelligent sensor systems
advanced intelligent control
intelligent decision support systems
prediction
machine learning
IoT technologies
cyberphysical systems
IT Industry 4.0 paradigm
IoT and the Digital Age with 5G communications
Intelligent Cyber Enterprise
Smart City
intelligent sensors applied to rescue robots
firefighting robots
rehabilitation robots
robot-assisted surgery
domestic robots

Published Papers (3 papers)

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Research

21 pages, 13685 KiB

Open AccessArticle

A Unified Multimodal Interface for the RELAX High-Payload Collaborative Robot

by Luca Muratore, Arturo Laurenzi, Alessio De Luca, Liana Bertoni, Davide Torielli, Lorenzo Baccelliere, Edoardo Del Bianco and Nikos G. Tsagarakis

Sensors 2023, 23(18), 7735; https://doi.org/10.3390/s23187735 - 07 Sep 2023

Viewed by 963

Abstract

This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human–Robot Collaboration (HRC) tasks requiring high-level interaction forces on a real-world scale. The proposed multimodal framework is capable of combining physical interaction, Ultra Wide-Band (UWB) radio sensing, a Graphical User Interface (GUI), verbal control, and gesture interfaces, combining the benefits of all these different modalities and allowing humans to accurately and efficiently command the RELAX mobile cobot and collaborate with it. The effectiveness of the multimodal interface is evaluated in scenarios where the operator guides RELAX to reach designated locations in the environment while avoiding obstacles and performing high-payload transportation tasks, again in a collaborative fashion. The results demonstrate that a human co-worker can productively complete complex missions and command the RELAX mobile cobot using the proposed multimodal interaction framework. Full article

(This article belongs to the Special Issue Versatile Intelligent Portable Interfaces for Human-Robot Interaction Systems)

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24 pages, 1352 KiB

Open AccessArticle

An Intelligent Platform for Software Component Mining and Retrieval

by Nazia Bibi, Tauseef Rana, Ayesha Maqbool, Farkhanda Afzal, Ali Akgül and Manuel De la Sen

Sensors 2023, 23(1), 525; https://doi.org/10.3390/s23010525 - 03 Jan 2023

Cited by 1 | Viewed by 1404

Abstract

The development of robotic applications necessitates the availability of useful, adaptable, and accessible programming frameworks. Robotic, IoT, and sensor-based systems open up new possibilities for the development of innovative applications, taking advantage of existing and new technologies. Despite much progress, the development of these applications remains a complex, time-consuming, and demanding activity. Development of these applications requires wide utilization of software components. In this paper, we propose a platform that efficiently searches and recommends code components for reuse. To locate and rank the source code snippets, our approach uses a machine learning approach to train the schema. Our platform uses trained schema to rank code snippets in the top k results. This platform facilitates the process of reuse by recommending suitable components for a given query. The platform provides a user-friendly interface where developers can enter queries (specifications) for code search. The evaluation shows that our platform effectively ranks the source code snippets and outperforms existing baselines. A survey is also conducted to affirm the viability of the proposed methodology. Full article

(This article belongs to the Special Issue Versatile Intelligent Portable Interfaces for Human-Robot Interaction Systems)

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17 pages, 626 KiB

Open AccessArticle

A Dynamic Multi-Mobile Agent Itinerary Planning Approach in Wireless Sensor Networks via Intuitionistic Fuzzy Set

by Tariq Alsboui, Richard Hill, Hussain Al-Aqrabi, Hafiz Muhammad Athar Farid, Muhammad Riaz, Shamaila Iram, Hafiz Muhammad Shakeel and Muhammad Hussain

Sensors 2022, 22(20), 8037; https://doi.org/10.3390/s22208037 - 21 Oct 2022

Cited by 12 | Viewed by 1221

Abstract

In recent research developments, the application of mobile agents (MAs) has attracted extensive research in wireless sensor networks (WSNs) due to the unique benefits it offers, such as energy conservation, network bandwidth saving, and flexibility of open usage for various WSN applications. The majority of the proposed research ideas on dynamic itinerary planning agent-based algorithms are efficient when dealing with node failure as a result of energy depletion. However, they generate inefficient groups for MAs itineraries, which introduces a delay in broadcasting data return back to the sink node, and they do not consider the expanding size of the MAs during moving towards a sequence of related nodes. In order to rectify these research issues, we propose a new Graph-based Dynamic Multi-Mobile Agent Itinerary Planning approach (GDMIP). GDMIP works with “Directed Acyclic Graph” (DAG) techniques and distributes sensor nodes into various and efficient group-based shortest-identified routes, which cover all nodes in the network using intuitionistic fuzzy sets. MAs are restricted from moving in the predefined path and routes and are responsible for collecting data from the assigned groups. The experimental results of our proposed work show the effectiveness and expediency compared to the published approaches. Therefore, our proposed algorithm is more energy efficient and effective for task delay (time). Full article

(This article belongs to the Special Issue Versatile Intelligent Portable Interfaces for Human-Robot Interaction Systems)

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