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Design, Analysis, and Experiment of a Coupled-Adaptive Underactuated Prosthetic Handbased on Linkage Mechanisms

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SSRN

SSRN 2022年

作者： Fan, Shaowei Dai, Jinghui Zhang, Ning Zhang, Ting Cheng, Ming Liu, Bingchen Jiang, Li State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150080 China National Research Center for Rehabilitation Technical Aids Beijing100176 China College of Mechanical and Electrical Engineering Soochow University Jiangsu Suzhou215021 China

To reproduce the characteristics of human hand motion, this paper proposes a novel four-degree-of-freedom prosthetic hand that combines the advantages of coupled motion and self-adaptive motion. A coupled-adaptive underactuated finger was developed using a cross-coupled four-link mechanism and an adaptive five-link mechanism. The finger can perform both power and precision grasping excellently. Based on the seesaw mechanism, a differential mechanism among the middle finger, ring finger, and little finger was developed to further reduce the size and weight of the prosthetic hand. To avoid the ejection phenomenon, the stability of the finger is systematically analyzed in this paper using the grasp-state space analysis technique. The stability analysis results indicate that ejection does not occur in the entire workspace of the proposed finger. The grasping experiments indicate that the proposed prosthetic hand possesses excellent stability and adaptability. © 2022, The Authors. All rights reserved.

关键词： Prosthetics

Intelligent Fault Diagnosis Using Limited Data Under Different Working Conditions Based on SEflow Model and Data Augmentation 16th

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Intelligent Fault Diagnosis Using Limited Data Under Differe...

16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Li, Sijue Peng, Gaoliang Mao, Daoyong Zhu, Zhiyu Ji, Mengyu Chen, Yuanhang State Key Laboratory of Robotics and System Harbin Institute of Technology No. 92 Xidazhi Street Harbin Heilongjiang Province150001 China China Electronics Technology Group Corporation no. 38 Research Institute Hefei Anhui Province China Department of Computer Science City University of Hong Kong Hong Kong

ISBN: (纸本)9789813364196

Accurate fault diagnosis of machine components is quite important for normal operation of equipment. Nowadays, artificial intelligent methods have been widely researched in fault diagnosis of rolling element bearings (REB). However, due to the variation of machine working conditions, the diagnosis accuracy always degrade seriously. Besides, as it is really hard to achieve large amounts of labeled health condition signals from real equipment, data deficiency is another trouble. Both issues impede the practical application of data-driven fault diagnosis. So as to solve the problems, a data augmentation method SEflow based on squeeze-and-excitation networks (SEnet) and flow-generative model is proposed. Proposed SEflow can learn the data distributions from limited data, then generate augmented signals among different machine working conditions. The experiments applied on bearing datasets and ball screw signals verify the effectiveness of proposed method on solving domain adaption and data deficiency. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

Hardware Programming of a Single-input Pneumatic Mechanism to Control Multiple Elastic Inflatable Actuators

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Hardware Programming of a Single-input Pneumatic Mechanism t...

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Ningbin Zhang Guoying Gu Xiangyang Zhu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University and Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781665431545

Elastic inflatable actuators (EIAs) are widely used in the emerging field of soft robotics. Although integrating multiple EIAs in soft robots has been demonstrated successful, these EIAs typically require independent control inputs that results in a complex actuation process. This paper proposes a single-input pneumatic mechanisms (SIPM) to generate a wide range of output pressures via hardware programming, enabling multiple EIAs to achieve different motions. We first present a conceptual design of the SIPM and build its pneumatic model based on air compressibility, which relates the control inputs, the structural parameters of the SIPM, and the output pressures. Then, we perform a series of parametric analyses and numerical simulations to investigate the hardware programming of structural parameters for target output pressures. Finally, a SIPM prototype whose structural parameters are derived from simulation results is developed. The experimental results validate the effectiveness of the proposed mechanism.

关键词： Actuators Atmospheric modeling Simulation Prototypes Process control Programming Predictive models

A novel method of combining computer vision, eye-tracking, EMG, and IMU to control dexterous prosthetic hand

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A novel method of combining computer vision, eye-tracking, E...

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Shi, Chunyuan Qi, Le Yang, Dapeng Zhao, Jingdong Liu, Hong Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150081 China Artificial Intelligence Laboratory State Key Laboratory of Robotics and System Harbin150081 China

ISBN: (纸本)9781728163215

Due to poor robustness, instability, and the heavy burden of use, the traditional myoelectric control method is still powerless in the face of the control of the dexterous prosthetic hand. To solve this problem, a new method (CVEEI), that combines computer vision, eye tracking, electromyogram (EMG) and IMU was proposed in this paper. Firstly, through gazing (eye-tracking) in front of the screen, the grasping pattern of the objects can be fed back to the prosthetic hand controller;Then, the prosthetic hand can be controlled to transport the object to the position expected, on collaboration of both EMG and IMU. In this process, the grasping pattern of all objects can be recognized by computer vision in real-time. Importantly, through comparing the traditional EMG control method (co-contraction to switch) in the transport experiment of the objects, the superiority of this new method in operating the dexterous prosthetic hand was further verified (fast > 1s/single object) in this paper. © 2019 IEEE.

关键词： Eye tracking

Multi-kernel Correntropy Regression: Robustness, Optimality, and Application on Magnetometer Calibration

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arXiv 2023年

作者： Li, Shilei Chen, Yihan Lou, Yunjiang Shi, Dawei Li, Lijing Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China The School of Automation Beijing Institute of Technology China The School of Information and Control Engineering China University of Mining and Technology China

This paper investigates the robustness and optimality of the multi-kernel correntropy (MKC) on linear regression. We first derive an upper error bound for a scalar regression problem in the presence of arbitrarily large outliers and state that the kernel bandwidth plays an important role in minimizing the lowest upper error bound. Then, we find that the proposed MKC is related to a specific heavy-tail distribution, where its head shape is consistent with the Gaussian distribution but its tail shape is heavy-tailed, and the extent of heavy-tail is controlled by the kernel bandwidth. It becomes a Gaussian distribution when the bandwidth is infinite, which allows one to tackle both Gaussian and non-Gaussian problems without explicitly investigating the noise distributions. To explore the optimal underlying distribution parameters, an expectation-maximization-like (EM) algorithm is developed to estimate the parameter vectors and the distribution parameters in an alternating manner. The results show that our algorithm can achieve equivalent performance compared with the traditional linear regression under Gaussian noise, and it significantly outperforms the conventional method under heavy-tailed noise. Both numerical simulations and experiments on a magnetometer calibration application verify the effectiveness of the proposed method. Note to Practitioners-The goal of this paper is to enhance the accuracy of conventional linear regression in handling outliers while maintaining its optimality under Gaussian assumptions. Our algorithm is formulated under the maximum likelihood estimation (MLE) framework, assuming the regression residuals follow a type of heavy-tailed noise distribution with an extreme case of Gaussian. The degree of the heavy tail is explored alternatingly using an Expectation-Maximization (EM) algorithm which converges very quickly. The robustness and optimality of the proposed approach are investigated and compared with the traditional approaches. Both th

关键词： Linear regression

Maximize the foot clearance for a hopping robotic leg considering motor saturation

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arXiv 2021年

作者： Su, Juntong Jin, Bingchen Ye, Shusheng Ruan, Lecheng Sun, Caiming Ding, Ning Fu, Yili Luo, Jianwen Shenzhen518172 China Shenzhen518172 China Beijing100000 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150000 China

A hopping leg, no matter in legged animals or humans, usually behaves like a spring during the periodic hopping. Hopping like a spring is efficient and without the requirement of complicated control algorithms. Position and force control are two main methods to realize such a spring-like behaviour. The position control usually consumes the torque resources to ensure the position accuracy and compensate the tracking errors. In comparison, the force control strategy is able to maintain a high elasticity. Currently, the position and force control both leads to the discount of motor saturation ratio as well as the bandwidth of the control system, and thus attenuates the performance of the actuator. To augment the performance, this letter proposes a motor saturation strategy based on the force control to maximize the output torque of the actuator and realize the continuous hopping motion with natural dynamics. The proposed strategy is able to maximize the saturation ratio of motor and thus maximize the foot clearance of the single leg. The dynamics of the two-mass model is utilized to increase the force bandwidth and the performance of the actuator. A single leg with two degrees of freedom is designed as the experiment platform. The actuator consists of a powerful electric motor, a harmonic gear and encoder. The effectiveness of this method is verified through simulations and experiments using a robotic leg actuated by powerful high reduction ratio actuators. © 2021, CC BY-NC-ND.

关键词： Actuators

Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction

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arXiv 2023年

作者： Li, Qi Shen, Ziyi Li, Qian Barratt, Dean C. Dowrick, Thomas Clarkson, Matthew J. Vercauteren, Tom Hu, Yipeng Centre for Medical Image Computing Wellcome/EPSRC Centre for Interventional and Surgical Sciences Department of Medical Physics and Biomedical Engineering University College London London United Kingdom State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Biomedical Engineering & Imaging Sciences King’s College London London United Kingdom

Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In this paper, we first investigated two identified contributing factors of the learned inter-frame correlation that enable the DNN-based reconstruction: anatomy and protocol. We propose to incorporate the ability to represent these two factors - readily available during training - as the privileged information to improve existing DNN-based methods. This is implemented in a new multitask method, where the anatomical and protocol discrimination are used as auxiliary tasks. We further develop a differentiable network architecture to optimise the branching location of these auxiliary tasks, which controls the ratio between shared and task-specific network parameters, for maximising the benefits from the two auxiliary tasks. Experimental results, on a dataset with 38 forearms of 19 volunteers acquired with 6 different scanning protocols, show that 1) both anatomical and protocol variances are enabling factors for DNN-based US reconstruction;2) learning how to discriminate different subjects (anatomical variance) and predefined types of scanning paths (protocol variance) both significantly improve frame prediction accuracy, volume reconstruction overlap, accumulated tracking error and final drift, using the proposed algorithm. © 2023, CC BY.

关键词： Deep neural networks

Multi-kernel Correntropy-based Orientation Estimation of IMUs: Gradient Descent Methods

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arXiv 2023年

作者： Li, Shilei Li, Lijing Shi, Dawei Lou, Yunjiang Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Information and Control Engineering China University of Mining and Technology China The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China

This paper presents two computationally efficient algorithms for the orientation estimation of inertial measurement units (IMUs): the multi-kernel correntropy-based gradient descent (CGD) and the multi-kernel correntropy-based decoupled orientation estimation (CDOE). Traditional methods, such as gradient descent (GD) and decoupled orientation estimation (DOE), rely on the least square (LS) criterion in algorithm derivation, making them vulnerable to external acceleration and magnetic interference. To address this issue, we first demonstrate that the multi-kernel correntropy loss (MKCL) is an optimal objective function under the maximum likelihood estimation (MLE) framework when the noise follows a specific type of heavy-tailed distribution. Then, we provide some important properties of the MKCL as a cost function. By replacing the LS cost with the MKCL, we develop the CGD and CDOE algorithms. We evaluate the effectiveness of our proposed methods by comparing them with existing algorithms in various situations. Experimental results indicate that our proposed methods (CGD and CDOE) outperform their conventional counterparts (GD and DOE), especially when faced with external acceleration and magnetic disturbances. Furthermore, the new algorithms demonstrate significantly lower computational complexity than Kalman filter-based approaches, making them suitable for applications with low-cost microprocessors. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

Autonomous inverse encoding guides 4D nanoprinting for highly programmable shape morphing

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International Journal of Extreme Manufacturing 2025年第3期 472-488页

作者： Shuaiqi Ren Zhiang Zhang Ruokun He Jiahao Fan Guangming Wang Hesheng Wang Bing Han Yong-Lai Zhang Zhuo-Chen Ma Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Engineering University of Cambridge Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin University

Highly programmable shape morphing of 4D-printed micro/nanostructures is urgently desired for applications in robotics and intelligent systems. However, due to the lack of autonomous holistic strategies throughout the target shape input, optimal material distribution generation,and fabrication program output, 4D nanoprinting that permits arbitrary shape morphing remains a challenging task for manual design. In this study, we report an autonomous inverse encoding strategy to decipher the genetic code for material property distributions that can guide the encoded modeling toward arbitrarily pre-programmed 4D shape morphing. By tuning the laser power of each voxel at the nanoscale, the genetic code can be spatially programmed and controllable shape morphing can be realized through the inverse encoding process. Using this strategy, the 4D-printed structures can be designed and accurately shift to the target morphing of arbitrarily hand-drawn lines under stimulation. Furthermore, as a proof-of-concept, a flexible fiber micromanipulator that can approach the target region through pre-programmed shape morphing is autonomously inversely encoded according to the localized spatial *** strategy may contribute to the modeling and arbitrary shape morphing of micro/nanostructures fabricated via 4D nanoprinting, leading to cutting-edge applications in microfluidics, micro-robotics, minimally invasive robotic surgery, and tissue engineering.

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