Special Issue "Advanced Robots: Design, Control and Application"

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuators for Robotics".

Deadline for manuscript submissions: 20 September 2021.

Special Issue Editors

Prof. Dr. Ioan Doroftei
E-Mail Website
Guest Editor
Head of Mechanical Engineering, Mechatronics and Robotics Department, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania
Interests: robotic applications of shape memory alloys; modeling and simulation; mechanisms and machine theory; mechanical engineering; mobile robots, social robotics; rehabilitation robots
Special Issues and Collections in MDPI journals
Prof. Dr. Karsten Berns
E-Mail Website
Guest Editor
Head of Robotics Research Lab, Computer Science Department Technical University of Kaiserslautern, D-67653 Kaiserslautern, Germany
Interests: robot control architectures; autonomous driving and working; biologically motivated robots; mobile robots; humanoid robots; two-legged running; human-robot interaction

Special Issue Information

Dear Colleagues,

Research into the design, control and application of advanced robots has increased during the last few decades, with many different and interesting projects being developed. Advanced robots have many promising applications in various areas of modern society. These robots could yield significant positive impacts on society, but they also carry the potential to cause negative impacts. Therefore, these impacts should be considered and discussed from the perspectives of not only technical solutions but also relevant social issues including safety, law, ethics, psychology and philosophy.

Contributions from all fields related to advanced robots are welcome in this Special Issue, particularly the following:

  • Human–robot interactions (HRI) and social robotics;
  • Safety issues for advanced robots and autonomous systems;
  • Legal and ethical issues for advanced robots;
  • Advanced industrial robots for future manufacturing;
  • Healthcare and medical applications;
  • Service and assistance;
  • Entertainment and education;
  • Robotics and autonomous driving;
  • Artificial intelligence (AI) and robotics;
  • Bio-inspired robotics.

Prof. Dr. Ioan Doroftei
Prof. Dr. Karsten Berns
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 papers will be 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. Actuators is an international peer-reviewed open access monthly 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 1600 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

  • human–robot interactions (HRI)
  • safety issues
  • legal and ethical issues
  • advanced industrial robots
  • healthcare
  • service
  • education
  • autonomous driving
  • artificial intelligence (AI)
  • bio-inspired robotics

Published Papers (2 papers)

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Research

Article
Feedback Linearization of Inertially Actuated Jumping Robots
Actuators 2021, 10(6), 114; https://doi.org/10.3390/act10060114 - 29 May 2021
Viewed by 848
Abstract
Inertially Actuated Jumping Robots (IAJR) provide a promising new means of locomotion. The difficulty of IAJR is found in the hybrid nature of the ground contact/flying dynamics. Recent research studies in our Systems Lab have provided a family tree of inertially actuated locomotion [...] Read more.
Inertially Actuated Jumping Robots (IAJR) provide a promising new means of locomotion. The difficulty of IAJR is found in the hybrid nature of the ground contact/flying dynamics. Recent research studies in our Systems Lab have provided a family tree of inertially actuated locomotion systems. The proposed Tapping Robot is the most prompt member of this tree. In this paper, a feedback linearization controller is introduced to provide controllability given the 3-dimensional motion complexity. The research objective is to create a general controller that can regulate the locomotion of Inertially Actuated Jumping Robots. The expected results can specify a desired speed and/or jump height, and the controller ensures the desired values are achieved. The controller can achieve the greatest response for the Basketball Robot at a maximum jump height of 0.25 m, which is greater than the former performance with approximately 0.18 m. The design paradigm used on the Basketball Robot was extended to the Tapping Robot. The Tapping Robot achieved a stable average forward velocity of 0.0773 m/s in simulation and 0.157 m/s in experimental results, which is faster than the forward velocity of former robot, Pony III, with 0.045 m/s. Full article
(This article belongs to the Special Issue Advanced Robots: Design, Control and Application)
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Article
A Non-Linear Continuous-Time Generalized Predictive Control for a Planar Cable-Driven Parallel Robot
Actuators 2021, 10(5), 97; https://doi.org/10.3390/act10050097 - 04 May 2021
Cited by 1 | Viewed by 651
Abstract
This paper addresses a novel nonlinear algorithm for the trajectory tracking of a planar cable-driven parallel robot. In particular, we outline a nonlinear continuous-time generalized predictive control (NCGPC). The proposed controller design is based on the finite horizon continuous-time minimization of a quadratic [...] Read more.
This paper addresses a novel nonlinear algorithm for the trajectory tracking of a planar cable-driven parallel robot. In particular, we outline a nonlinear continuous-time generalized predictive control (NCGPC). The proposed controller design is based on the finite horizon continuous-time minimization of a quadratic predicted cost function. The tracking error in the receding horizon is approximated using a Taylor-series expansion. The main advantage of the proposed NCGPC is based on using an analytic solution, which can be truncated to a desired degree of order of the Taylor-series. This allows us to achieve a prediction horizon of NCGPC tracking performance. The description of the proposed NCGPC method is followed by a comparison between NCGPC and a conventional computed torque control (CTC) method. Robustness tests are performed by considering payload and parameter uncertainties for both controllers. Simulation results of NCGPC compared to the commonly used CTC prove the effectiveness and advantages of the proposed approach. Full article
(This article belongs to the Special Issue Advanced Robots: Design, Control and Application)
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