Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Intelligent Control and Applications for Robotics
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Intelligent Control and Applications for Robotics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 8053

Special Issue Editor

Dr. Fan Zhang

E-Mail Website
Guest Editor
The Research Center for Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
Interests: dynamics and control of rigid-flexible complex systems; underactuated system dynamics and control; multi-agent mutual positioning, collaborative decision-making planning and control

Special Issue Information

Dear Colleagues,

Robotics can help automate tasks that are repetitive, dangerous, or vulnerable to human error. More and more applications in totally different fields, like UAV, AUV, drones, mobile robots, space robots, for instance, make the robotics more versatile and further complicated. However, automation without intelligence creates a system that cannot respond to variables, new environments, or dynamic requirements. With advanced decision, planning, and control schemes, the plants will enrich the application scenarios.

The aim of this Special Issue is to bring together original research on the related topics.

Potential topics include Aerial Robotics, marine robotics, space robotics, and mobile robotics of the following aspect, but are not limited:

  • Advanced control algorithms
  • Intelligent decision and motion planning
  • Autonomous navigation and planning
  • Contact dynamic modeling
  • Sensors fusion and estimation
  • Multi-agents planning and control
  • Collaborative manipulation
  • Learning and classifying algorithms
  • Advanced robotics design and applications

Dr. Fan Zhang
Guest Editor

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. Applied Sciences 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

  • advanced control algorithms
  • intelligent decision and motion planning
  • autonomous navigation and planning
  • contact dynamic modeling
  • sensors fusion and estimation
  • multi-agents planning and control collaborative manipulation
  • learning and classifying algorithms
  • advanced robotics design and applications

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 2395 KiB  
Article
A Convolutional Neural Network-Based Broad Incremental Learning Filter for Attenuating Physiological Tremors in Telerobot Systems
by Guanyu Lai, Weizhen Liu, Weijun Yang and Yun Zhang
Appl. Sci. 2023, 13(2), 890; https://doi.org/10.3390/app13020890 - 9 Jan 2023
Cited by 2 | Viewed by 2016
Abstract
While master-slave teleoperated robotic systems have extensive applications in practice, the physiological tremors can easily affect the control accuracy and even destroy the stability of the closed-loop control systems during operation. Hence, the development of some effective approaches for counteracting physiological tremors is [...] Read more.
While master-slave teleoperated robotic systems have extensive applications in practice, the physiological tremors can easily affect the control accuracy and even destroy the stability of the closed-loop control systems during operation. Hence, the development of some effective approaches for counteracting physiological tremors is of both theoretical and practical importance. In this paper, a broad learning network-based filter integrating a deep learning network and modified incremental learning algorithms is proposed to reconstruct and compensate for tremor signals. To strengthen the recognition of correlations between different moments, the lateral connectivity structure is adopted to obtain multi-scale feature maps. Each feature window is obtained from multi-scale feature maps generated by the convolutional neural network, which has an advantage that makes the feature nodes fuse the feature information of long time series and short time series by the lateral connection. The broad learning network is a unique construction, which only needs to obtain the input and the output to conveniently calculate the connection weights by the pseudo-inverse without involving backpropagation. It is known that the relation between the data X and the label Y can be represented as XW=Y, and the solution W can be obtained by the pseudo-inverse W=X+Y. In addition, to guarantee the ill-posed problem, a ridge regression algorithm is used for the pseudo-inverse calculation. The effectiveness of our raised network architecture is illustrated by comparative simulation and experiment results. Full article
(This article belongs to the Special Issue Intelligent Control and Applications for Robotics)
►▼ Show Figures

Figure 1

13 pages, 2915 KiB  
Article
Comparative Study of Physics Engines for Robot Simulation with Mechanical Interaction
by Jaemin Yoon, Bukun Son and Dongjun Lee
Appl. Sci. 2023, 13(2), 680; https://doi.org/10.3390/app13020680 - 4 Jan 2023
Cited by 5 | Viewed by 5056
Abstract
Simulation with a reasonable physical model is important to develop control algorithms for robots quickly, accurately, and safely without damaging the associated physical systems in various environments. However, it is difficult to choose the suitable tool for simulating a specific project. To help [...] Read more.
Simulation with a reasonable physical model is important to develop control algorithms for robots quickly, accurately, and safely without damaging the associated physical systems in various environments. However, it is difficult to choose the suitable tool for simulating a specific project. To help users in selecting the best tool when simulating a given project, we compare the performance of the four widely used physics engines, namely, ODE, Bullet, Vortex, and MoJoco, for various simple and complex industrial scenarios. We first summarize the technical algorithms implemented in each physics engine. We also designed four simulation scenarios ranging from simple scenarios for which analytic solution exists to complex industrial scenarios to compare the performance of each physics engine. We then present the simulation results in the default settings of all the physics engines, and analyze the behavior and contact force of the simulated objects. Full article
(This article belongs to the Special Issue Intelligent Control and Applications for Robotics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop