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Actuators
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Design and Control of Actuators for Active Human−Machine Interaction
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Design and Control of Actuators for Active Human−Machine Interaction

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 9322

Special Issue Editors

Prof. Dr. Qing Guo

E-Mail Website
Guest Editor
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: electrohydraulics; exoskeleton
Special Issues, Collections and Topics in MDPI journals
Dr. Wei Yang

E-Mail Website
Guest Editor
Ningbo Innovation Center, Zhejiang University, Ningbo 315100, China
Interests: wearable robots; human-machine interaction; human-in-the-loop optimization; gait analysis

Special Issue Information

Dear Colleagues,

The aging of the population is currently a global challenge, and impaired upper/lower-limb motion is a prevalent feature in the elderly. In addition, some occupations, such as firemen and relief workers, require extra physical assistance in order to perform tasks efficiently. Wearable robots can support ambulatory functions in the elderly and augment human performance in healthy people during lifting or walking by providing assistive torques. The design and control of actuators is crucial in order to enhance the human–machine interaction performance. Recent advances in the design and control of quasi-direct drive actuators, nonlinear stiffness series elastic actuators and artificial muscles have demonstrated great potential regarding their ability to enhance the interaction performance of wearable robots.

This Special Issue aims to collect and present the latest results and novel methodologies proposed in the design and control of actuators, as well as applications and experiments related to wearable robots, such as upper-limb exoskeletons, hand exoskeletons, lower-limb exoskeletons, powered orthosis, powered prosthesis, etc. In addition, this Special Issue aims to share achievements regarding the application of actuators to specific scenarios that concern human–machine interaction, such as motor-driven fitness equipment, teleoperations with force feedback, virtual reality with physical interaction, etc. We encourage researchers and practitioners in this field to submit manuscripts related to, but not limited to, the following topics:

(1) Position/Force control for rigid/soft exoskeletons;

(2) Novel series elastic actuator (SEA), parallel elastic actuator (PEA), and hybrid elastic actuator (HEA);

(3) Quasi-direct drive (QDD) actuators;

(4) Actuators with variable impedance;

(5) Actuators with adjustable physical compliance;

(6) Artificial muscles designed for wearable robots;

(7) Actuation modules with energy harvest;

(8) Design and control of actuators applied in new scenarios.

Prof. Dr. Qing Guo
Dr. Wei Yang
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. 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 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

  • wearable robots
  • exoskeleton
  • human–machine interaction
  • compliant actuator
  • variable impedance

Published Papers (7 papers)

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Research

16 pages, 3375 KiB  
Article
Optimizing Exoskeleton Assistance: Muscle Synergy-Based Actuation for Personalized Hip Exoskeleton Control
by Yehao Ma, Dewei Liu, Zehao Yan, Linfan Yu, Lianghong Gui, Canjun Yang and Wei Yang
Actuators 2024, 13(2), 54; https://doi.org/10.3390/act13020054 - 31 Jan 2024
Viewed by 1272
Abstract
Exoskeleton robots hold promising prospects for rehabilitation training in individuals with weakened muscular conditions. However, achieving improved human–machine interaction and delivering customized assistance remains a challenging task. This paper introduces a muscle synergy-based human-in-the-loop (HIL) optimization framework for hip exoskeletons to offer more [...] Read more.
Exoskeleton robots hold promising prospects for rehabilitation training in individuals with weakened muscular conditions. However, achieving improved human–machine interaction and delivering customized assistance remains a challenging task. This paper introduces a muscle synergy-based human-in-the-loop (HIL) optimization framework for hip exoskeletons to offer more personalized torque assistance. Initially, we propose a muscle synergy similarity index to quantify the similarity of synergy while walking with and without the assistance of an exoskeleton. By integrating surface electromyography (sEMG) signals to calculate metrics evaluating muscle synergy and iteratively optimizing assistance parameters in real time, a muscle synergy-based HIL optimized torque configuration is presented and tested on a portable hip exoskeleton. Iterative optimization explores the optimal and suboptimal assistance torque profiles for six healthy volunteers, simultaneously testing zero torque and predefined assistance configurations, and verified the corresponding muscle synergy similarity indices through experimental testing. In our validation experiments, the assistance parameters generated through HIL optimization significantly enhance muscle synergy similarity during walking with exoskeletal assistance, with an optimal average of 0.80 ± 0.04 (mean ± std), marking a 6.3% improvement over prior assistive studies and achieving 96.4% similarity compared with free walking. This demonstrates that the proposed muscle synergy-based HIL optimization can ensure robotic exoskeleton-assisted walking as “natural” as possible. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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16 pages, 2530 KiB  
Article
Extended State Observer-Based Sliding Mode Control Design of Two-DOF Lower Limb Exoskeleton
by Jiyu Zhang, Wei Gao and Qing Guo
Actuators 2023, 12(11), 402; https://doi.org/10.3390/act12110402 - 27 Oct 2023
Cited by 3 | Viewed by 1286
Abstract
Due to some model uncertainties and unknown friction disturbances that exist in the 2-DOF lower limb exoskeleton, a linear extended state observer (LESO) is proposed to estimate the unmeasurable angular velocity of two joints and the lumped uncertainties caused by friction disturbance and [...] Read more.
Due to some model uncertainties and unknown friction disturbances that exist in the 2-DOF lower limb exoskeleton, a linear extended state observer (LESO) is proposed to estimate the unmeasurable angular velocity of two joints and the lumped uncertainties caused by friction disturbance and hydraulic parametric uncertainties. Meanwhile, by using the Lyapunov technique, a sliding mode controller is designed to improve the dynamic performance and the steady state accuracy of two joint angle responses in human–exoskeleton cooperative motion. By regulating the sliding mode controller gain, both the system state errors and estimation errors of the LESO are reduced in an arbitrary boundary of zero neighborhood. Finally, the effectiveness of the proposed control scheme is verified with both simulation and experimental results for one operator-wearable test, to guarantee that the joint position tracking performance and human–exoskeleton impedance torques are suppressed in a satisfactory boundary. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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14 pages, 2880 KiB  
Article
Modelling and RBF Control of Low-Limb Swinging Dynamics of a Human–Exoskeleton System
by Xinyu Peng, Shujun Zhang, Mengling Cai and Yao Yan
Actuators 2023, 12(9), 353; https://doi.org/10.3390/act12090353 - 6 Sep 2023
Viewed by 961
Abstract
With the increase in the elderly population in China and the growing number of individuals who are unable to walk normally, research on lower limb exoskeletons is becoming increasingly important. This study proposes a complete dynamic model parameter identification scheme for the human–machine [...] Read more.
With the increase in the elderly population in China and the growing number of individuals who are unable to walk normally, research on lower limb exoskeletons is becoming increasingly important. This study proposes a complete dynamic model parameter identification scheme for the human–machine coupling model of lower limb exoskeletons. Firstly, based on the coupling model, the excitation trajectory is optimized, data collection experiments are conducted, and the dynamic parameter vector of the system is identified using the least squares method. Secondly, this lays the foundation for designing adaptive control based on RBF neural network approximation. Thirdly, the Lyapunov function is used to prove that the RBF neural network adaptive controller can achieve stable tracking of the lower limb exoskeleton. Finally, simulation analysis reveals that increasing the gains of the RBF controllers effectively reduces tracking errors. Furthermore, the tracking errors and control torques show that adaptive control based on the RBF neural network approximation works well. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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19 pages, 4749 KiB  
Article
Research on Machine Vision-Based Control System for Cold Storage Warehouse Robots
by Zejiong Wei, Feng Tian, Zhehang Qiu, Zhechen Yang, Runyang Zhan and Jianming Zhan
Actuators 2023, 12(8), 334; https://doi.org/10.3390/act12080334 - 20 Aug 2023
Viewed by 1241
Abstract
In recent years, the global cold chain logistics market has grown rapidly, but the level of automation remains low. Compared to traditional logistics, automation in cold storage logistics requires a balance between safety and efficiency, and the current detection algorithms are poor at [...] Read more.
In recent years, the global cold chain logistics market has grown rapidly, but the level of automation remains low. Compared to traditional logistics, automation in cold storage logistics requires a balance between safety and efficiency, and the current detection algorithms are poor at meeting these requirements. Therefore, based on YOLOv5, this paper proposes a recognition and grasping system for cartons in cold storage warehouses. A human–machine interaction system is designed for the cold storage environment, enabling remote control and unmanned grasping. At the algorithm level, the CA attention mechanism is introduced to improve accuracy. The Ghost lightweight module replaces the CBS structure to enhance runtime speed. The Alpha-DIoU loss function is utilized to improve detection accuracy. With the comprehensive improvements, the modified algorithm in this study achieves a 0.711% increase in mAP and a 0.7% increase in FPS while maintaining accuracy. Experimental results demonstrate that the CA attention mechanism increases fidelity by 2.32%, the Ghost lightweight module reduces response time by 13.89%, and the Alpha-DIoU loss function enhances positioning accuracy by 7.14%. By incorporating all the improvements, the system exhibits a 2.16% reduction in response time, a 4.67% improvement in positioning accuracy, and a significant overall performance enhancement. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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16 pages, 3756 KiB  
Article
A Bionic Control Method for Human–Exoskeleton Coupling Based on CPG Model
by Tianyi Sun, Shujun Zhang, Ruiqi Li and Yao Yan
Actuators 2023, 12(8), 321; https://doi.org/10.3390/act12080321 - 9 Aug 2023
Viewed by 1180
Abstract
Exoskeleton robots are functioning in contexts with more complicated motion control needs as a result of the technology and applications for these robots rapidly developing. This calls for novel control techniques to accommodate their employment in a range of real-world settings. This paper [...] Read more.
Exoskeleton robots are functioning in contexts with more complicated motion control needs as a result of the technology and applications for these robots rapidly developing. This calls for novel control techniques to accommodate their employment in a range of real-world settings. This paper proposes a bionic control method for a human–exoskeleton coupling dynamic model based on the CPG model, utilizing a model on the dynamics of the human–exoskeleton interaction. The CPG network is established as an oscillator by two neurons inhibiting one another, which approximates the torques simulated in the inverse dynamic analysis as the input to the exoskeleton robot. The findings of the simulation assessment suggest that the bionic control strategy may improve the robot’s ability to move quickly and steadily, as well as better adapt to challenging environments. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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17 pages, 3563 KiB  
Article
Research on Identifying Robot Collision Points in Human–Robot Collaboration Based on Force Method Principle Solving
by Zhijun Wang, Bocheng Zhu, Yue Yang and Zhanxian Li
Actuators 2023, 12(8), 320; https://doi.org/10.3390/act12080320 - 9 Aug 2023
Viewed by 1002
Abstract
After years of more rigid and conventional production processes, the traditional manufacturing industry has been moving toward flexible manufacturing and intelligent manufacturing in recent years. After more than half a century of development, robotics has penetrated into all aspects of human production and [...] Read more.
After years of more rigid and conventional production processes, the traditional manufacturing industry has been moving toward flexible manufacturing and intelligent manufacturing in recent years. After more than half a century of development, robotics has penetrated into all aspects of human production and life, bringing significant changes to the development of human society. At the same time, the key technology of human–machine cooperative operation has become a research hotspot, and how to realize a human–machine integrated safety system has attracted attention. Human–machine integration means that humans and robots can work in the same natural space, coordinating closely and interacting naturally. To realize real human–robot integration under human–robot cooperative operation, the good judgment of intentional interaction and accidental collision and the detection of collision joints and collision points when accidental collision occurs are the key points. In this paper, we propose a method to identify the collision joints by detecting real-time current changes in each joint of the robot and solve the collision point location information of the collision joints through the principle of virtual displacement and the principle of force method using the force sensor data installed at the base of the robot as the known condition. The results show that the proposed method of identifying the collision joints using changes in joint current and then establishing a collision detection algorithm to solve the collision point location is correct and reliable. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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22 pages, 17504 KiB  
Article
A Large Force Haptic Interface with Modular Linear Actuators
by Yeongtae Jung and Joao Ramos
Actuators 2023, 12(7), 293; https://doi.org/10.3390/act12070293 - 18 Jul 2023
Viewed by 1631
Abstract
This paper presents a haptic interface with modular linear actuators that addresses the limitations of conventional devices based on rotary joints. The proposed haptic interface is composed of parallel linear actuators that provide high backdrivability and small inertia. The performance of the haptic [...] Read more.
This paper presents a haptic interface with modular linear actuators that addresses the limitations of conventional devices based on rotary joints. The proposed haptic interface is composed of parallel linear actuators that provide high backdrivability and small inertia. The performance of the haptic interface is compared to those of conventional mechanisms in terms of force capability, reflected inertia, and structural stiffness. High stiffness, large range of motion, and high force capability, which are in trade-off relationships in traditional haptic interfaces, are achieved. The device can apply up to 83 N continuously, i.e., three-fold more than most haptic devices. The theoretical minimum haptic force density and stiffness of the proposed mechanism are 1.3 to 1.9 and 37 times those of the conventional mechanisms under similar conditions, respectively. The system is scalable because the structural stiffness depends on only the timing belt stiffness, whereas that of conventional haptic interfaces is inversely proportional to the cube of the structural length. The modular actuator enables changes in the degrees of freedom (DOFs) for different applications. The proposed haptic interface was tested through an interaction experiment in a virtual environment with virtual walls. Full article
(This article belongs to the Special Issue Design and Control of Actuators for Active Human−Machine Interaction)
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