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Research Square 2021年

作者： Xu, Yundou Yang, Fan Mei, Youen Zhang, Dongsheng Zhou, Yulin Zhao, Yongsheng Laboratory of Parallel Robot and Mechatronic System of Hebei Province Yanshan University Qinhuangdao066004 China Key Laboratory of Advanced Forging & Stamping Technology Science of Ministry of National Education Yanshan University Qinhuangdao006004 China School of Mechanical Engineering Yanshan University Qinhuangdao066004 China Tencent Robotics X Tencent Holdings Shenzhen518057 China

In the present study, the over-constrained hybrid manipulator R(2RPR)R/SP+RR is considered as the research objective. In this paper, kinematics of the hybrid manipulator, including the forward and inverse position, are analyzed. Then, the workspace is checked based on the inverse position solution to evaluate whether the workspace of the hybrid manipulator meets the requirements, and the actual workspace of the hybrid robot is analyzed. After that, the force analysis of the over-constrained parallel mechanism is carried out, and an ADAMS-ANSYS rigid-flexible hybrid body model is established to verify the simulation. Based on the obtained results from the force analysis, the manipulator structure is design. Then, the structure optimization is carried out to improve the robot stiffness. Finally, calibration and workspace verification experiments are performed on the prototype, cutting experiment of an S-shaped aluminum alloy workpiece is completed, and the experiment verifies the processing ability of the prototype and proves that the prototype has good application prospects. © 2021, CC BY.

关键词： Kinematics

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Grip Force Perception Based on dAENN for Minimally Invasive Surgery Robot

Grip Force Perception Based on dAENN for Minimally Invasive ...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Guo, Yongchen Pan, Bo Fu, Yili Meng, Max Q.-H. Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin Heilongjiang China Chinese University of Hong Kong Department of Electronic Engineering Hong Kong

ISBN: (纸本)9781728163215

Although robot assisted minimally invasive surgery brings the gospel to patients, force perception is gone. Among all the contact forces during surgery, the instrument grip force plays the most important role. In this paper, a grip force perception method based on denoising AutoEncoder Neural Network (dAENN) is proposed. The method utilizes sensor data including encoder readings and motor current over a time window as the input of dAENN for sufficient information. An Artificial Neural Network (ANN) is then introduced as a machine learning tool to learn the nonlinear mapping between the compact features and grip force labels. Feature extraction is first introduced into grip force perception problem in this paper. Experiment results shows adequate expressive capability of the extracted coding as well as the superior grip force perception performance over several popular data-based methods under the same dataset. © 2019 IEEE.

关键词： Neural networks

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A Local Dynamic Path Planning Approach for WMRs Based on Fuzzy Dual CHOMP 9

A Local Dynamic Path Planning Approach for WMRs Based on Fuz...

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9th IEEE International Conference on Cyber Technology in Automation, Control and Intelligent systems, CYBER 2019

作者： Li, Zhi Ding, Liang You, Bo Gao, Haibo Mechanical Power Engineering College Harbin University of Science and Technology Harbin China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (纸本)9781728107691

Wheeled mobile robots (WMRs) are widely utilized in exploration tasks on different planets. The path planning technique is required to guide a WMR to a target point or region. A new path planning method in a dynamic environment is proposed. The method improves the original dual Covariant Hamiltonian Optimization for Motion Planning (CHOMP) method by a fuzzy reasoning module and Nonmonotone Gradient Projection Algorithm (NGPA). Thus, this method can achieve low cost paths while maintaining the accessibility of each path nodes. The method to establish local dynamic cost map based on a new velocity-based artificial potential field (VAPF) is proposed as the environment for path planning. Thus, the low cost paths can guide a WMR away from obstacles. Results of the simulations show that the path planning method can dynamically generate a smooth path for a WMR to avoid obstacles. © 2019 IEEE.

关键词： Mobile robots

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3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

arXiv

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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain Stimulation Electrode Implantation

Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain...

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IEEE International Conference on robotics and Biomimetics

作者： Weihang Huang Shenghao Dai Anze Xu Xianyi He Shaoping Huang Anzhu Gao School of Mechanical Engineering Shanghai Jiao Tong University Shanghai Jiao Tong University Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China the Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665405362

Deep brain stimulation (DBS) has been widely used in clinical practice as an effective therapy for neurological disorders. MR-conditional robot-assisted electrode implantation has attracted more attention for DBS because of its great accuracy and high-quality guiding images by using MRI. This paper develops a pneumatically actuated MR-safe parallel robot for deep brain electrode implantation. Its fully plastic components and MR-safe pneumatic actuators enable the robotic system to be MR-safe, posing no known hazards in MR environment. A 6-DOF parallel robot is developed using six slider-crank mechanisms for prismatic motions. Inverse kinematics is built to investigate its workspace and achieve the precise control. Experiments are carried out to validate the feasibility, and results shows that the average error of the motion is 0.11 mm. The developed parallel robot shows the potential advantages in the automatic and precise robot-assisted neurosurgical surgery in future.

关键词： Electrodes Pneumatic actuators Neurological diseases Parallel robots Magnetic resonance imaging Satellite broadcasting Deep brain stimulation

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Mechanical design of a 4-DOF minimally invasive surgical instrument

Mechanical design of a 4-DOF minimally invasive surgical ins...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Li, Kun Li, Jihua Li, Lei Ji, Shuai Meng, Xianju Fu, Yili Shandong Jianzhu University School of Mechanical and Electronic Engineering Jinan250101 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150080 China

ISBN: (纸本)9781728163215

In order to meet design requirements in minimally invasive surgery (MIS), it is necessary to conduct basic operations in the narrow working space. Taking a grasper for example, a 4DOF MIS instrument driven by servo motors and transmitted by cables is designed. The design of the end of surgical instrument driven by cables is suitable for long-distance transmission, which improves dexterity of the surgical instrument working in narrow space. The mechanism principle including the wrist, graspers and shaft rolling are described. Kinematic coupling between the wrist and grasper are analyzed. Prototype of the surgical instrument is presented. This instrument prototype can be applied in most MIS operations. © 2019 IEEE.

关键词： Cables

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Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy

arXiv

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arXiv 2021年

作者： Wu, Zicong Lou, Chuqian Jin, Zhu Huang, Shaoping Liu, Ning Zou, Yun Kovac, Mirko Gao, Anzhu Yang, Guang-Zhong Institute of Medical Robotics Department of Bioengineering Shanghai Jiao Tong University Shanghai200240 China Imperial College London Empa Swiss Federal Laboratories for Materials Science and Technology Limited Hong Kong999077 Hong Kong Aerial Robotics Laboratory Imperial College London LondonSW7 2AZ United Kingdom Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments. © 2021, CC BY-NC-SA.

关键词： Electrospinning

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Delay estimation for cortical-muscular interaction via the rate of voxels change

Delay estimation for cortical-muscular interaction via the r...

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IEEE International Conference on systems, Man and Cybernetics

作者： Jinbiao Liu Gansheng Tan Yixuan Sheng Jiaole Wang Wenjie Lu Honghai Liu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China School of Computing University of Portsmouth Portsmouth UK

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

It is evident that corticomuscular coherence (CMC), representing the functional coupling between motor cortex and muscle tissues, plays a crucial role in neurophysiologic studies and applications. It is hypothesized that there is an unknown time delay comprising at least neural conduction time in the process of corticomuscular interaction. In this study, we developed a novel delay estimation method, defined as the rate of voxels change (RVC) for the estimation of time delay in two coupled physiological signals. The RVC is the dynamic variation of the local CMCs observed in different time offsets. Both simulation and physiological data confirm the capability of RVC in estimating cortical-muscular delay. The underlying mechanisms of individual discrepancy of the latency is also investigated via exploring the correlation between delays, brain activity and motor performance. Correlation analyses indicate an intrinsic link between the connectivity strength of the brain network and the length of time delay in cortical-muscular interactions.

关键词： Correlation Delay effects Delay estimation Muscles Brain modeling Physiology Data models

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Feature Fusion of sEMG and Ultrasound Signals in Hand Gesture Recognition

Feature Fusion of sEMG and Ultrasound Signals in Hand Gestur...

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IEEE International Conference on systems, Man and Cybernetics

作者： Jia Zeng Yu Zhou Yicheng Yang Jiaole Wang Honghai Liu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China School of Computing University of Portsmouth Portsmouth UK

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

Multi-modal sensory fusion is believed to obtain higher accuracy in gesture recognition. Its difficulty lies in mining discriminative features and fusing features from different modalities. Surface electromyography(sEMG) and ultrasound signals are typical signal modalities in gesture recognition. It is expected that the fusion of them can take advantage of the complementarity of electrophysiological information and muscle morphology information. This paper proposed two kinds of feature fusion method. The one is concatenating the manual designed sEMG and ultrasound features, and the other is a convolutional neural network (CNN) based feature exaction and fusion method for sEMG and ultrasound signals. Eight able-bodied subjects were involved to participate in the experiments. In the experiments, four channels of sEMG and A-mode ultrasound signals corresponding to 20 gestures were collected synchronously to evaluate the proposed method. The experimental results demonstrated that the fusion sEMG-ultrasound feature always outperformed the separate sEMG or ultrasound feature regardless of the feature extraction method, and as for fusion sEMG-ultrasound feature, the CNN based method achieve a high accuracy (97.38±1.49%) in 20 gestures, which surpassed the method of concatenating the manual designed features and applying machine learning algorithm (LDA, KNN, SVM).

关键词： Support vector machines Ultrasonic imaging Surface morphology Gesture recognition Manuals Feature extraction Task analysis

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Mechanics of soft-body rolling motion without external torque

arXiv

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arXiv 2024年

作者： Liang, Xudong Ding, Yimiao Yuan, Zihao Jiang, Junqi Xie, Zongling Fei, Peng Sun, Yixuan Gu, Guoying Zhong, Zheng Chen, Feifei Si, Guangwei Gong, Zhefeng School of Science Harbin Institute of Technology Shenzhen518055 China Department of Neurology The Fourth Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Hangzhou310058 China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence Zhejiang University 1369 West Wenyi Road Hangzhou311121 China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang University Hangzhou310058 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Brain and Cognitive Science Institute of Biophysics Chinese Academy of Sciences 15 Datun Road Beijing100101 China University of Chinese Academy of Sciences 19A Yuquan Road Beijing100049 China Huazhong University of Science and Technology Optical and Electronic Information Wuhan430074 China Zhejiang Lab. Hangzhou311121 China

The Drosophila larva, a soft-body animal, can bend its body and roll efficiently to escape danger. However, contrary to common belief, this rolling motion is not driven by the imbalance of gravity and ground reaction forces. Through functional imaging and ablation experiments, we demonstrate that the sequential actuation of axial muscles within an appropriate range of angles is critical for generating rolling. We model the interplay between muscle contraction, hydrostatic skeleton deformation, and body-environment interactions, and systematically explain how sequential muscle actuation generates the rolling motion. Additionally, we constructed a pneumatic soft robot to mimic the larval rolling strategy, successfully validating our model. This mechanics model of soft-body rolling motion not only advances the study of related neural circuits, but also holds potential for applications in soft robotics. © 2024, CC BY.

关键词： Pneumatics

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