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Electronics
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Advanced Technologies in Autonomous Robotic System
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Advanced Technologies in Autonomous Robotic System

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (28 September 2023) | Viewed by 4671

Special Issue Editors

Dr. Ting Zou

E-Mail Website
Guest Editor
Department of Mechanical and Mechatronics Engineering, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
Interests: mechatronics; intelligent systems; nonlinear motion control
Special Issues, Collections and Topics in MDPI journals
Dr. Xing Wu

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering， Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: intelligent perception and control; mobile robot design; navigation and control; coordinated control and system scheduling of multiple mobile robots; intelligent electromechanical equipment and systems
Dr. Marco Cognetti

E-Mail Website
Guest Editor
Department of Electronic Engineering, National University of Ireland Maynooth, Maynooth, Ireland
Interests: (active) state estimation; shared autonomy / human-robot interaction; localization and control of a team of heterogeneous robot; motion planning

Special Issue Information

Dear Colleagues,

The past years have witnessed significant improvements in the development of autonomous robotic systems, along with advances in artificial intelligence (AI), human-robot interaction, sensing technology, and dynamic system control methodologies. Endowed with inherent advantages of autonomy, the latest autonomous robotic systems showcase great advantages in numerous applications, including autonomous navigation, autonomous manufacturing, human-robot interaction, and social robots emerging in recent years. Along with the tremendous technical advancements and widespread applications, the development of state-of-the-art autonomous robotic systems is a complex topic that involves a wide range of research realms such as sensing technology, robot control, mechanism design, and kinematic and dynamic modeling, among others.

This Special Issue focuses on providing an overview of the recent advances covering a wide realm of advanced technologies in autonomous robotic systems. This Special Issue highly welcomes original papers on the theoretical advancements and practical applications of autonomous robotic systems. Review papers or tutorial papers on this topic are also encouraged.

Dr. Ting Zou
Dr. Xing Wu
Dr. Marco Cognetti
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. Electronics 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 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

  • mechanism design
  • artificial intelligence
  • autonomous robot
  • human-robot interaction
  • control
  • dynamics and kinematics
  • sensing
  • robot modelling

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Published Papers (2 papers)

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Research

22 pages, 2826 KiB  
Article
Research on Resource Allocation of Autonomous Swarm Robots Based on Game Theory
by Zixiang He, Yi Sun and Zhongyuan Feng
Electronics 2023, 12(20), 4370; https://doi.org/10.3390/electronics12204370 - 22 Oct 2023
Cited by 2 | Viewed by 1207
Abstract
To address the issue of resource allocation optimization in autonomous swarm robots during emergency situations, this paper abstracts the problem as a two-stage extended game. In this game, participants are categorized as either resource-providing robots or resource-consuming robots. The strategies of the resource-providing [...] Read more.
To address the issue of resource allocation optimization in autonomous swarm robots during emergency situations, this paper abstracts the problem as a two-stage extended game. In this game, participants are categorized as either resource-providing robots or resource-consuming robots. The strategies of the resource-providing robots involve resource production and pricing, whereas the strategies of the resource-consuming robots consist of determining the quantity to be purchased based on resource pricing. In the first stage of the game, the resource-providing robots use the Cournot game to determine the resource production according to market supply and demand conditions; in the second stage of the game, the resource-providing robots and the resource-consuming robots play the price game and establish the utility function of the swarm robots to seek the optimal pricing and the optimal purchasing strategy of the swarm robots. After the mathematical derivation, this paper demonstrates the existence of a single Nash equilibrium in the constructed game. Additionally, the inverse distributed iterative search algorithm solves the game’s optimal strategy. Finally, simulation verifies the game model’s validity. This study concludes that the designed game mechanism enables both sides to reach equilibrium and achieve optimal resource allocation. Full article
(This article belongs to the Special Issue Advanced Technologies in Autonomous Robotic System)
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17 pages, 6644 KiB  
Article
Multi-Objective Multi-Learner Robot Trajectory Prediction Method for IoT Mobile Robot Systems
by Fei Peng, Li Zheng, Zhu Duan and Yu Xia
Electronics 2022, 11(13), 2094; https://doi.org/10.3390/electronics11132094 - 4 Jul 2022
Cited by 7 | Viewed by 2643
Abstract
Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as [...] Read more.
Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as base learners, including autoregressive moving average, multi-layer perceptron, Elman neural network, deep echo state network, and long short-term memory. A non-dominated sorting genetic algorithm III is applied to automatically combine these base learners, generating an accurate and robust ensemble model. The proposed model is tested on several actual robot trajectory datasets and evaluated by several metrics. Moreover, different existing optimization algorithms are also applied to compare with the proposed model. The results demonstrate that the proposed model can achieve satisfactory accuracy and robustness for different datasets. It is suitable for the accurate prediction of robot trajectory. Full article
(This article belongs to the Special Issue Advanced Technologies in Autonomous Robotic System)
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