Fluid-driven artificial muscles: bio-design, manufacturing, sensing, control, and applications

Zhang, Chao; Zhu, Pingan; Lin, Yangqiao; Wei, Tang; Zhang, Jiao; Yang, Huayong; Zou, Jun

doi:10.1007/s42242-020-00099-z

Cited by 50 publications

(26 citation statements)

References 170 publications

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“…One end of the muscle is fixed; the other one moves and applies the contractile force. PAMs can be adopted for rehabilitation robots [30] and in industrial applications [31]. For achieving the motion of a joint, PAMs are usually mounted to work in three possible actuation configurations: agonistic-antagonistic, parallel and bio-inspired [30].…”

Section: The Application Contextmentioning

confidence: 99%

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

et al. 2022

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The fast-growing human–robot collaboration predicts that a human operator could command a robot without mechanical interface if effective communication channels are established. In noisy, vibrating and light sensitive environments, some sensors for detecting the human intention could find critical issues to be adopted. On the contrary, biological signals, as electromyographic (EMG) signals, seem to be more effective. In order to command a laboratory collaborative robot powered by McKibben pneumatic muscles, promising actuators for human–robot collaboration due to their inherent compliance and safety features have been researched, a novel modeling-based electromyographic signal (MBES) classifier has been developed. It is based on one EMG sensor, a Myotrac one, an Arduino Uno and a proper code, developed in the Matlab environment, that performs the EMG signal recognition. The classifier can recognize the EMG signals generated by three hand-finger movements, regardless of the amplitude and time duration of the signal and the muscular effort, relying on three mathematical models: exponential, fractional and Gaussian. These mathematical models have been selected so that they are the best fitting with the EMG signal curves. Each of them can be assigned a consent signal for performing the wanted pick-and-place task by the robot. An experimental activity was carried out to test and achieve the best performance of the classifier. The validated classifier was applied for controlling three pressure levels of a McKibben-type pneumatic muscle. Encouraging results suggest that the developed classifier can be a valid command interface for robotic purposes.

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Section: The Application Contextmentioning

confidence: 99%

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

et al. 2022

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“…However, most of the existing stretchable sensors have limited stretchability, and their structure is also vulnerable to repeated contact or deformation. [ 366,367 ] This is mainly due to lack of ideal stretchable conductive materials, and there seems to be a balance between the conductivity and softness. Using conductive liquids, e.g., conductive silver ink, [ 368 ] liquid metal, [ 369 ] or even sodium chloride (NaCl) solution, [ 370 ] may be a promising way to break the balance.…”

Section: Human–robot Interactionmentioning

confidence: 99%

Intelligent Soft Surgical Robots for Next‐Generation Minimally Invasive Surgery

Zhu

Lyu

et al. 2021

Advanced Intelligent Systems

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Endowed with the expected visions for future surgery, minimally invasive surgery (MIS) has become one of the most rapid developing areas in modern surgery. Soft robotics, which originates from interdisciplinary advances in materials, fabrication, and electronics, featuring better adaptability and safer interaction, holds great promises in addressing current technical challenges in MIS, which are difficult to be solved with current rigid robotic technologies. For the first time, herein, the expected characteristics of next-generation MIS from the surgeons' perspectives are analyzed and the recent progress of soft surgical instruments from three different aspects is comprehensively summarized: engineering design, fabrication techniques, and human-robot interaction. Perspectives of nextgeneration soft surgical robots are then discussed, where some exciting possibilities are emphasized. It is believed that further developments of intelligent soft robotics enable the next-generation MIS to agilely navigate to the target and conduct dexterous diagnostic or therapeutic procedures without any trade-offs in invasiveness and ultimately be a propitious solution for future surgery.

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“…advanced robot skin can be applied to various complex contours of cobots by deforming itself while maintaining its sensing performance [44], [45]. In addition to the sensibilities, the powerful robot skin can also integrate with actuation function enabled by biological muscles to obtain specific functionalities, for example, the variable stiffness [46]. Future skin-covered cobots are coupled robotic systems composed of rigid, flexible, and soft sensing components and actuation mechanisms [20].…”

Section: A New Paradigm Of Robot Skin Coupled With Actuatorsmentioning

confidence: 99%

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

Pang

Yang

Pang

2021

IEEE Trans. Med. Robot. Bionics

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The emerging applications of collaborative robots (cobots) are spilling out from product manufactories to service industries for human care, such as patient care for combating the coronavirus disease 2019 (COVID-19) pandemic and in-home care for coping with the aging society. There are urgent demands on equipping cobots with safe collaboration, immersive teleoperation, affective interaction, and other features (e.g., energy autonomy and self-learning) to make cobots capable of these application scenarios. Robot skin, as a potential enabler, is able to boost the development of cobots to address these distinguishing features from the perspective of multimodal sensing and self-contained actuation. This review introduces the potential applications of cobots for human care together with those demanded features. In addition, the explicit roles of robot skin in satisfying the escalating demands of those features on inherent safety, sensory feedback, natural interaction, and energy autonomy are analyzed. Furthermore, a comprehensive review of the recent progress in functionalized robot skin in components level, including proximity, pressure, temperature, sensory feedback, and stiffness tuning, is presented. Results show that the codesign of these sensing and actuation functionalities may enable robot skin to provide improved safety, intuitive feedback, and natural interfaces for future cobots in human care applications. Finally, open challenges and future directions in the real implementation of robot skin and its system synthesis are presented and discussed.

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Fluid-driven artificial muscles: bio-design, manufacturing, sensing, control, and applications

Cited by 50 publications

References 170 publications

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

Intelligent Soft Surgical Robots for Next‐Generation Minimally Invasive Surgery

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

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