Augmented virtual stiffness rendering of a cable-driven SEA for human-robot interaction

Yu, Ningbo; Zou, Wulin; Tan, Wen; Yang, Zhuo

doi:10.1109/jas.2017.7510637

Cited by 12 publications

(5 citation statements)

References 28 publications

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“…In this paper, a cable-driven series elastic actuator (SEA) system that has been used in our previous works [21], [22], [27], [28], is used for simulation and experimental validation. Its mechanical design is shown in Fig.…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction

Zou

Duan²,

Chen

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Variable impedance control is advantageous for physical human-robot interaction to improve safety, adaptability and many other aspects. This paper presents a gainscheduled variable stiffness control approach under strict frequency-domain constraints. Firstly, to reduce conservativeness, we characterize and constrain the impedance rendering, actuator saturation, disturbance/noise rejection and passivity requirements into their specific frequency bands. This relaxation makes sense because of the restricted frequency properties of the interactive robots. Secondly, a gain-scheduled method is taken to regulate the controller gains with respect to the desired stiffness. Thirdly, the scheduling function is parameterized via a nonsmooth optimization method. Finally, the proposed approach is validated by simulations, experiments and comparisons with a gain-fixed passivity-based PID method.

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Section: Simulation and Experimental Resultsmentioning

confidence: 99%

Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction

Zou

Duan²,

Chen

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Self Cite

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“…Through experiments, Malallah et al will learn that the robot receives the hand gesture instructions and makes corresponding speech according to the actions of these instructions ( 5 ). Yu et al solved the rendering problem caused by the introduction of elastic elements on the basis of human-computer interaction technology through experiments ( 6 ). Li and Wang compared traditional school physical education teaching through experimental research and pointed out the shortcomings of traditional physical education teaching.…”

Section: Related Workmentioning

confidence: 99%

Human-computer interactive physical education teaching method based on speech recognition engine technology

Sang

Xing-quan

2022

Front. Public Health

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With the advent of the era of artificial intelligence, speech recognition engine technology has a profound impact on social production, life, education, and other fields. Voice interaction is the most basic and practical type of human-computer interaction. To build an intelligent and automatic physical education teaching mode, this paper combines human-computer interaction based on speech recognition technology with physical education teaching. Students input through voice signals, and the system receives signals, analyzes signals, recognizes signals, and feeds back information to students in multiple forms. For the system to process the external speech signal, this paper uses the Mel cepstral coefficient algorithm to extract the speech information. By comparing the speech recognition rate and antinoise rate of Hidden Markov Model, Probabilistic Statistics Neural Network, and Hybrid Model (Hidden Markov and Rate Statistical Neural Network combination), the speech recognition engine uses the hybrid model, and its speech recognition rate is 98.3%, and the average antinoise rate can reach 85%. By comparing the human-computer interaction physical education teaching method with the traditional teaching method, the human-computer interaction method is superior to the traditional teaching method in the acquisition of physical knowledge, the acquisition of physical skills, the satisfaction of physical education courses and the ability of active learning. It effectively solves the drawbacks of traditional physical education and rationally uses human-computer interaction technology. On the basis of not violating physical education, realize the diversification of physical education, improve the quality of teaching, improve students' individual development and students' autonomous learning ability. Therefore, the combination of human-computer interaction and physical education based on recognition engine technology is the trend of today's physical education development.

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“…Various SEAs have been developed and applied for physical human-robot interaction, such as the Bowden-cablebased SEA for the lower extremity powered exoskeleton (LOPES) [4], the MR-compatible SEA for wrist sensorimotor study [5], the SEA for a monopod hopping robot [6], the compact SEA for upper and lower limb rehabilitation [7], the Bowden-cable SEA for hand finger exoskeleton [8]- [10], etc. The cable-driven SEA allows to detach the actuation motor from the robot frame, enables power transmission to remote place, and brings conveniences and flexibilities into system construction and control for applications to physical humanrobot interaction [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

Passivity guaranteed stiffness control with multiple frequency band specifications for a cable-driven series elastic actuator

Zou

Sun

2019

Mechanical Systems and Signal Processing

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Impedance control and specifically stiffness control are widely applied for physical human-robot interaction. The series elastic actuator (SEA) provides inherent compliance, safety and further benefits. This paper aims to improve the stiffness control performance of a cable-driven SEA. Existing impedance controllers were designed within the full frequency domain, though human-robot interaction commonly falls in the low frequency range. We enhance the stiffness rendering performance under formulated constraints of passivity, actuator limitation, disturbance attenuation, noise rejection at their specific frequency ranges. Firstly, we reformulate this multiple frequencyband optimization problem into the H∞ synthesis framework. Then, the performance goals are quantitatively characterized by respective restricted frequency-domain specifications as norm bounds. Further, a structured controller is directly synthesized to satisfy all the competing performance requirements. Both simulation and experimental results showed that the produced controller enabled good interaction performance for each desired stiffness varying from 0 to 1 times of the physical spring constant. Compared with the passivity-based PID method, the proposed H∞ synthesis method achieved more accurate and robust stiffness control performance with guaranteed passivity.

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Augmented virtual stiffness rendering of a cable-driven SEA for human-robot interaction

Cited by 12 publications

References 28 publications

Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction

Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction

Human-computer interactive physical education teaching method based on speech recognition engine technology

Passivity guaranteed stiffness control with multiple frequency band specifications for a cable-driven series elastic actuator

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