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Electronics
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Intelligent Perception and Control for Robotics
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Intelligent Perception and Control for Robotics

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

Deadline for manuscript submissions: 15 June 2025 | Viewed by 1943

Special Issue Editors

Dr. Qi Zou

E-Mail Website
Guest Editor
Robotics Engineering, College of Letters and Sciences, Columbus State University, Columbus, GA 31907, USA
Interests: parallel robotics; medical robot; mechatronics; solid mechanics; linkage mechanism and innovative mechanical design
Dr. Guanyu Huang

E-Mail Website
Guest Editor
Zhejiang Laboratory, Intelligent Robotics Research Center, Hangzhou 311121, China
Interests: bipedal robot control; fault tolerant control; Integrated drive joint system
Dr. Zhibo Sun

E-Mail Website
Guest Editor
Engineering Training Center, Beihang University, Beijing 100191, China
Interests: robotics and mechatronics: kinematic and dynamic analysis, the wheel-legged and boinic robots, generalized parallel mechanisms research; artificial intelligence for robotics: machine learning, deep learning, machine vision for robotics; pneumatic research: pneumatic system control, quasi-zero stiffness air spring, pneumatic vibration isolator; intelligent manufacturing: flexible manufacturing, vision-based assembly system
Special Issues, Collections and Topics in MDPI journals
Dr. Chonggang Du

E-Mail Website
Guest Editor
School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: multibody dynamics and control; flexible system; space tether

Special Issue Information

Dear Colleagues,

Robots play an important role in daily life and industrial applications. There is continuously increasing interest in robot systems, both in academic research institutions and at industrial sites. Traditional robotics provides a time-efficient, low-cost, high-precision, and reliable solution to manufacturing processes, while conventional robot systems have less impact in other scenarios. With the rapid development of highly integrated robot systems, robots are supplied with more diverse and complicated functions via intelligent perception and control methodologies. In industry, some advanced and autonomous robots are able to deal with specific operations, even in a time-dependent environment. These robots can carry out tasks in collaboration with other robots or professional workers, which can significantly expand their applications to a higher level. Robots are becoming popular in our daily lives, especially with the integration of artificial intelligence (AI). Service robots can deliver food, provide essential guidance, and communicate with customers in restaurants, shopping malls, or banks. Some commercial robot products serve as healthcare robots or assistive robots with impressive performance.

Robot systems are becoming ‘smarter’ due to the application of advanced sensor fusion, intelligent control strategies, highly integrated algorithms, and AI. This phenomenon comes from the cross-disciplinary cooperation of mechanical engineering, electrical engineering, mechatronics, computer science, software engineering, etc. The objectives of this Special Issue are to explore the latest research addressing theoretical or experimental breakthroughs in the field of robot perception and control strategies. High-quality original research articles and review articles are welcome. Research topics include but are not limited to the following:

  • Robotics and automation;
  • SLAM (Simultaneous Localization and Mapping);
  • Human–robot interaction;
  • Parallel robotics;
  • Autonomous vehicle/robot system;
  • Motion and control of humanoid robot;
  • Industrial robot;
  • Intelligent healthcare robot and assistive robot;
  • Intelligent motion control;
  • Sensor fusion of robot sytems;
  • Sensing and action of mobile robot;
  • Perception and control of legged robot;
  • Remote sensing and control of drone and underwater robot;
  • Robot system with high precision;
  • Robot vision system;
  • Machine learning and artificial intelligence in robotics;
  • Service robot based on artificial intelligence;
  • Multibody dynamics and control;
  • Teleoperation of space robotics;
  • Fault tolerant analysis and control;
  • Flexible robot;
  • Coexisting-cooperative-cognitive Robots;
  • Surgical teleoperation;
  • Swarm intelligence;
  • Multimodal perception in robot systems;
  • Compliance control for robotics;
  • Human–robot collaboration in industry.

Dr. Qi Zou
Dr. Guanyu Huang
Dr. Zhibo Sun
Dr. Chonggang Du
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

  • robotics
  • human–robot interaction
  • parallel robotics
  • medical robot

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Published Papers (2 papers)

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Research

15 pages, 11432 KiB  
Article
A Triangular Structure Constraint for Pedestrian Positioning with Inertial Sensors Mounted on Foot and Shank
by Jianyu Wang, Jing Liang, Chao Wang, Wanwei Tang, Mingzhe Wei and Yiling Fan
Electronics 2024, 13(22), 4496; https://doi.org/10.3390/electronics13224496 - 15 Nov 2024
Viewed by 318
Abstract
To suppress pedestrian positioning drift, a velocity constraint commonly known as zero-velocity update (ZUPT) is widely used. However, it cannot correct the error in the non-zero velocity interval (non-ZVI) or observe heading errors. In addition, the positioning accuracy will be further affected when [...] Read more.
To suppress pedestrian positioning drift, a velocity constraint commonly known as zero-velocity update (ZUPT) is widely used. However, it cannot correct the error in the non-zero velocity interval (non-ZVI) or observe heading errors. In addition, the positioning accuracy will be further affected when a velocity error occurs in the ZVI (e.g., foot tremble). In this study, the foot, ankle, and shank were regarded as a triangular structure. Consequently, an angle constraint was established by utilizing the sum of the internal angles. Moreover, in contrast to the traditional ZUPT algorithm, a velocity constraint method combined with Coriolis theorem was constructed. Magnetometer measurements were used to correct heading. Three groups of experiments with different trajectories were carried out. The ZUPT method of the single inertial measurement unit (IMU) and the distance constraint method of dual IMUs were employed for comparisons. The experimental results showed that the proposed method had high accuracy in positioning. Furthermore, the constraints built by the lower limb structure were applied to the whole gait cycle (ZVI and non-ZVI). Full article
(This article belongs to the Special Issue Intelligent Perception and Control for Robotics)
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16 pages, 8532 KiB  
Article
Automatic Parkinson’s Disease Diagnosis with Wearable Sensor Technology for Medical Robot
by Miaoxin Ji, Renhao Ren, Wei Zhang and Qiangwei Xu
Electronics 2024, 13(14), 2816; https://doi.org/10.3390/electronics13142816 - 17 Jul 2024
Viewed by 901
Abstract
The clinical diagnosis of Parkinson’s disease (PD) has been the subject of medical robotics research. Currently, a hot research topic is how to accurately assess the severity of Parkinson’s disease patients and enable medical robots to better assist patients in the rehabilitation process. [...] Read more.
The clinical diagnosis of Parkinson’s disease (PD) has been the subject of medical robotics research. Currently, a hot research topic is how to accurately assess the severity of Parkinson’s disease patients and enable medical robots to better assist patients in the rehabilitation process. The walking task on the Unified Parkinson’s Disease Rating Scale (UPDRS) is a well-established diagnostic criterion for PD patients. However, the clinical diagnosis of PD is determined based on the clinical experience of neurologists, which is subjective and inaccurate. Therefore, in this study, an automated diagnostic method for PD based on an improved multiclass support vector machine (MCSVM) is proposed in which wearable sensors are used. Kinematic analysis was performed to extract gait features, both spatiotemporal and kinematic, from the installed IMU and pressure sensors. Comparison experiments of three different kernel functions and linear trajectory experiments were designed. The experimental results show that the accuracies of the three kernel functions of the proposed improved MCSVM are 92.43%, 93.45%, and 95.35%. The simulation trajectories of the MCSVM are the closest to the real trajectories, which shows that the technique performs better in the clinical diagnosis of PD. Full article
(This article belongs to the Special Issue Intelligent Perception and Control for Robotics)
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