Intelligence Control and Applications of Intelligence Robotics
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 20 October 2024 | Viewed by 7158
Special Issue Editors
Interests: robust control; embedded system; robot control
Special Issue Information
Dear Colleagues,
With the advancements made in artificial intelligence and robotics, intelligent control has become an essential area of research. Intelligent control deals with the development of algorithms that can control a system's behavior in order to achieve the desired objectives, while adapting to changing environments.
In recent years, there has been a significant increase in the application of intelligent control in robotics. Robotics has become an integral part of our lives, and intelligent robots are being used in various fields, including manufacturing, healthcare, and agriculture, among others. The integration of intelligent control in robotics has led to the development of intelligent robots that are capable of performing complex tasks and adapting to dynamic environments.
This Special Issue focuses on the recent advancements in intelligent control and its applications in the field of robotics. The issue includes research papers that provide insights into the current state-of-the-art techniques in intelligent control and their applications in robotics. The topics covered in this Special Issue include, but are not limited to, the following:
- Intelligent control theory for robotic systems
- Learning-based approaches for intelligent control
- Multi-agent intelligent control for robotics
- Applications of intelligent control in autonomous robots
- Intelligent control for collaborative robots
- Human–robot interaction with intelligent control
- Intelligent control for swarm robotics
- Robust control theory
- Network control system
Dr. Bumyong Park
Prof. Dr. Won Il Lee
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
- intelligent control
- robotics
- artificial intelligence
- learning-based approaches
- autonomous robots
- multi-agent control
- collaborative robots
- human–robot interaction
- swarm robotics
- industrial robots
- robust control
- network control system
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Integrated Neural Network Approach for Enhanced Vital Signal Analysis Using CW Radar
Authors: Won Yeol Yoon; Nam Kyu Kwon
Affiliation: Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
Abstract: This study introduces a novel approach for analyzing vital signals using continuous-wave (CW) radar, employing an integrated neural network model to overcome the limitations associated with traditional step-by-step signal processing methods. Conventional methods for vital signal monitoring, such as electrocardiograms (ECGs) and sphygmomanometers, require direct contact and impose constraints on specific scenarios. Conversely, our study primarily focused on non-contact measurement techniques, particularly those using CW radar, which is known for its sim-plicity but faces challenges such as noise interference and complex signal processing. To address these issues, we propose a temporal convolutional network (TCN)-based framework that seam-lessly integrates noise removal, demodulation, and fast Fourier transform (FFT) processes into a single neural network. This integration minimizes cumulative errors and processing time, which are common drawbacks of conventional methods. The TCN was trained using a dataset compris-ing preprocessed in-phase and quadrature (I/Q) signals from the CW radar and corresponding heart rates measured via ECG. The performance of the proposed method was evaluated based on the L1 loss and accuracy against the moving average of the estimated heart rates. The results in-dicate that the proposed approach has the potential for efficient and accurate non-contact vital signal analysis, opening new avenues in health monitoring and medical research. Additionally, the integration of CW radar and neural networks in our framework offers a robust and scalable solution, enhancing the practicality of non-contact health monitoring systems in diverse environ-ments. This technology can be leveraged in healthcare robots to provide continuous and unobtru-sive monitoring of patients' vital signs, enabling timely interventions and improving overall pa-tient care.