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12th RSI International Conference on robotics and Mechatronics, ICRoM 2024

作者： Hamzeh, Hamed Shahroozi, Kiarash Nabipour, Ahmad Kazemi, Parham Malek-Zahedi, Mohammad Hallajian, Mehdi Moradia, Hadi School of Electrical and Computer Engineering College of Engineering University of Tehran Advanced Robotics and Intelligent Systems Laboratory Iran

ISBN: (纸本)9798331529734

Traditional puppet manipulation systems often require human operators to be physically present in tight and cramped locations. This leads to challenges in the positioning and effective operation of puppets, particularly in the presence of children in educational settings. In this paper, we present the design, development, and integration of a cost-effective robotic system for remotely manipulating puppets in real-time. Additionally, the system integrates a YOLOv8 Pose Detection model, trained on a custom dataset with an accuracy of 91.4%, enabling real-time gesture recognition and allowing the robot to be controlled by imitating the motions of a manually operated puppet. The system demonstrates the potential for many applications, including interactive entertainment, teleoperation, and education. © 2024 IEEE.

关键词： Gesture recognition

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Process planning and contour-based error compensation for precision grinding of miniature scalpels

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先进制造进展（英文版） 2024年第1期12卷 108-123页

作者： Cheng Fan Cao-Yang Xue Jun Zhao Wei Jiang Wen-Ge Han Lei Zhang Li-Ning Sun Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electrical EngineeringSoochow UniversitySuzhou 215021JiangsuPeople's Republic of China Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical and Electrical EngineeringZhejiang UniversityHangzhou 310027People's Republic of China State Key Laboratory of Intelligent Equipment and Manufacturing School of Mechanical EngineeringZhejiang University of TechnologyHangzhou 310023People's Republic of China

Miniature scalpels are mainly used in microsur-geries such as ophthalmic and cardiovascular *** size of a miniature scalpel is only a few millimeters,and the precision of the blade shape is high,which makes pro-duction of miniature scalpels extremely *** study proposes a new sharpening process for grinding miniature scalpels on a four-axis machine tool.A post-processing algo-rithm for a four-axis grinding machine based on a kinemat-ics model is *** then propose a corresponding parameter calibration method for the parameters used in the kinematics *** of possible errors in the param-eter calibration,a contour-based error compensation method is proposed for accurate adjustments to the edge shape fol-lowing *** can solve the problem of large devia-tions between the actual edge shape after grinding and the ideal edge *** effectiveness of the proposed process planning and error compensation method is verified experi-mentally,and the grinding process parameters of the minia-ture scalpel are optimized to improve its surface processing *** sharpness of the optimized miniature scalpel is less than 0.75 N,and the blade shape is symmetrical,which meets the technical requirements of miniature scalpels.

关键词： Miniature scalpel Sharpening Kinematics Error compensation Grinding

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Integrated Cross-Scale Manipulation and Modulable Encapsulation of Cell-Laden Hydrogel for Constructing Tissue-Mimicking Microstructures

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Research 2025年第1期2024卷 704-717页

作者： Yanfeng Zhao Xinyi Dong Yang Li Juan Cui Qing Shi Hen-Wei Huang Qiang Huang Huaping Wang Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Peking University First Hospital Xicheng DistrictBeijing 100034China Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of EducationNorth University of ChinaTaiyuan 030051China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Laboratory for Translational Engineering Harvard Medical SchoolCambridgeMA 02139USA Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of EducationBeijing 100081China

Engineered microstructures that mimic in vivo tissues have demonstrated great potential for applications in regenerative medicine,drug screening,and cell behavior ***,current methods for engineering microstructures that mimic the multi-extracellular matrix and multicellular features of natural tissues to realize tissue-mimicking microstructures in vitro remain ***,we propose a versatile method for constructing tissue-mimicking heterogeneous microstructures by orderly integration of macroscopic hydrogel exchange,microscopic cell manipulation,and encapsulation ***,various cell-laden hydrogel droplets are manipulated at the millimeter scale using electrowetting on dielectric to achieve efficient hydrogel ***,the cells are manipulated at the micrometer scale using dielectrophoresis to adjust their density and arrangement within the hydrogel ***,the photopolymerization of these hydrogel droplets is triggered in designated regions by dynamically modulating the shape and position of the excitation ultraviolet ***,heterogeneous microstructures with different extracellular matrix geometries and components were constructed,including specific cell densities and *** resulting heterogeneous microstructure supported long-term culture of hepatocytes and fibroblasts with high cell viability(over 90%).Moreover,the density and distribution of the 2 cell types had significant effects on the cell proliferation and urea *** propose that our method can lead to the construction of additional biomimetic heterogeneous microstructures with unprecedented potential for use in future tissue engineering applications.

关键词： cell behavior explorationhowevercurrent tissue mimicking microstructures cell laden hydrogel electrowetting dielectric regenerative medicinedrug screeningand heterogeneous microstructures engineered microstructures orderly integration

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A Novel Fish-inspired Self-adaptive Approach to Collective Escape of Swarm Robots Based on Neurodynamic Models

A Novel Fish-inspired Self-adaptive Approach to Collective E...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Junfei Li Simon X. Yang Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph Guelph Canada

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Fish schools present high-efficiency group behaviors to collective migration and dynamic escape from the predator through simple individual interactions. The purpose of this research is to infuse swarm robots with "fish-like" intelligence that will enable safe navigation and efficient cooperation, and successful completion of escape tasks in changing environments. In this paper, a novel fish-inspired self-adaptive approach is proposed for the collective escape of swarm robots. A bio-inspired neural network (BINN) is introduced to generate collision-free escape trajectories through the dynamics of neural activity and the combination of attractive and repulsive forces. In addition, a neurodynamics-based self-adaptive mechanism is proposed to improve the self-adaptive performance of the swarm robots in dynamic environments. Similar to fish escape maneuvers, simulations and real-robot experiments show that the swarm robots can collectively leave away from the threat and respond to sudden environmental changes. Several comparison studies demonstrated that the proposed approach can significantly improve the effectiveness, efficiency, and flexibility of swarm robots in complex environments.

关键词： Uncertainty Navigation Biological system modeling Dynamics Neural activity Swarm robotics Trajectory

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Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

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engineering 2022年第10期17卷 232-243页

作者： Zihang Gao Guanglu Jia Hongzhao Xie Qiang Huang Toshio Fukuda Qing Shi Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China

Existing biomimetic robots can perform some basic rat-like movement primitives(MPs)and simple behavior with stiff combinations of these *** mimic typical rat behavior with high similarity,we propose parameterizing the behavior using a probabilistic model and movement ***,an analysis of fifteen 10 min video sequences revealed that an actual rat has six typical behaviors in the open field,and each kind of behavior contains different bio-inspired combinations of eight *** used the softmax classifier to obtain the behavior-movement hierarchical probability ***,we specified the MPs using movement parameters that are static and *** obtained the predominant values of the static and dynamic movement parameters using hierarchical clustering and fuzzy C-means clustering,*** predominant parameters were used for fitting the rat spinal joint trajectory using a second-order Fourier series,and the joint trajectory was generalized using a back propagation neural network with two hidden ***,the hierarchical probability model and the generalized joint trajectory were mapped to the robot as control policy and commands,*** implemented the six typical behaviors on the robot,and the results show high similarity when compared with the behaviors of actual rats.

关键词： Biomimetic Bio-inspired robot Neural network learning system Behavior generation

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Design of a Remote Controlled Puppet Robot Imitating a Manual Driven Puppet Using Deep Learning Pose Detection

Design of a Remote Controlled Puppet Robot Imitating a Manua...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Hamed Hamzeh Kiarash Shahroozi Ahmad Nabipour Parham Kazemi Mohammad Malek-zahedi Mehdi Hallajian Hadi Moradia Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering College of Engineering University of Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

关键词： Hands Mechatronics Education Entertainment industry Manuals Gesture recognition Real-time systems Maintenance Robots intelligent control

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Dynamic Obstacle Avoidance for Magnetic Helical Microrobots Based on Deep Reinforcement Learning

Dynamic Obstacle Avoidance for Magnetic Helical Microrobots ...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Qiu, Yukang Hou, Yaozhen Yang, Haotian Gao, Yigao Huang, Hen-Wei Shi, Qing Huang, Qiang Wang, Huaping Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China Harvard Medical School Laboratory for Translational Engineering CambridgeMA02139 United States Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798350372601

Magnetic helical microrobots hold immense promise in biomedical domains owing to their compact size and efficient propulsion capabilities. However, navigating these microrobots through dynamic and unstructured environments, particularly when encountering numerous dynamic obstacles, remains a formidable challenge. In the study, a control framework based on deep reinforcement learning (DRL) with the objective of guiding a microrobot through dynamic obstacles towards specified target goals is introduced. Initially, we design and fabricate a microdrill capable of propulsion via external magnetic rotating fields produced by our magnetic actuation system. Subsequently, we construct a custom training environment, adhering to the OpenAI gym interface, to serve as the simulator for training purposes. Utilizing the proximal policy optimization algorithm, we conduct training of the navigation policy within this simulator. Simulations and experimental validations conducted in dynamic environments affirms the efficacy of the proposed method. © 2024 IEEE.

关键词： Microrobots

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A bionic approach for the mechanical and electrical decoupling of an MEMS capacitive sensor in ultralow force measurement

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Frontiers of Mechanical engineering 2023年第2期18卷 297-317页

作者： Wendi GAO Bian TIAN Cunlang LIU Yingbiao MI Chen JIA Libo ZHAO Tao LIU Nan ZHU Ping YANG Qijing LIN Zhuangde JIANG Dong SUN State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265599China State Key Laboratory of Robotics and Systems(HIT) Harbin 150006China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Department of Biomedical Engineering City University of Hong KongHong KongChina

Capacitive sensors are efficient tools for biophysical force measurement,which is essential for the exploration of cellular ***,attention has been rarely given on the influences of external mechanical and internal electrical interferences on capacitive *** this work,a bionic swallow structure design norm was developed for mechanical decoupling,and the influences of structural parameters on mechanical behavior were fully analyzed and optimized.A bionic feather comb distribution strategy and a portable readout circuit were proposed for eliminating electrostatic *** instability was evaluated,and electrostatic decoupling performance was verified on the basis of a novel measurement method utilizing four complementary comb arrays and applicationspecific integrated circuit *** electrostatic pulling experiment showed that the bionic swallow structure hardly moved by 0.770 nm,and the measurement error was less than 0.009% for the area-variant sensor and 1.118% for the gap-variant sensor,which can be easily compensated in *** proposed sensor also exhibited high resistance against electrostatic rotation,and the resulting measurement error dropped below 0.751%.The rotation interferences were less than 0.330 nm and(1.829×10^(-7))°,which were 35 times smaller than those of the traditional differential *** on the proposed bionic decoupling method,the fabricated sensor exhibited overwhelming capacitive sensitivity values of 7.078 and 1.473 pF/μm for gap-variant and area-variant devices,respectively,which were the highest among the current *** immunity to mechanical disturbances was maintained simultaneously,i.e.,less than 0.369% and 0.058% of the sensor outputs for the gap-variant and area-variant devices,respectively,indicating its great performance improvements over existing devices and feasibility in ultralow biomedical force measurement.

关键词： micro-electro-mechanical system capacitive sensor bionics operation instability mechanical and electrical decoupling biomedical force measurement

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EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-LSTM Hybrid Model

EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-L...

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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Cao, Wujing Guo, Xinqiang Zou, Yupeng Zhang, Shuo Luo, Mingxiang Kobsiriphat, Worawarit Wu, Xinyu Yin, Meng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems China School of Mechanical Engineering China University of Petroleum China National Metal and Materials Technology Center Thailand

ISBN: (纸本)9798350355123

Stroke, as one of the leading causes of long-term disability globally, often results in motor impairments, particularly in the hands, significantly affecting patients' daily activities and causing profound psychological trauma. Rehabilitation gesture recognition, as one of the key means of active rehabilitation medicine, holds significant potential in stroke rehabilitation, providing real-time feedback on patient progress and enabling personalized interventions to meet individual needs. Traditional gesture recognition methods face numerous challenges when dealing with stroke patient data, such as noise, motion blur, and individual differences. To address these challenges, this paper proposes a novel approach for stroke patient gesture recognition using deep learning models. We adopt a strategy combining denoising autoencoder (DAE), convolutional neural network (CNN), and long short-term memory (LSTM) to enhance the accurate recognition of hand movements in stroke patients. Specifically, DAE is utilized for denoising EMG signals, extracting features, and reducing noise to improve the signal's noise resistance. CNN is employed for spatial feature extraction, while LSTM captures temporal dependencies in gesture sequences. By integrating these three deep learning models, our aim is to enhance the accuracy and robustness of rehabilitation gesture recognition. We validate the proposed method's effectiveness on an EMG dataset from seven subjects through experiments and compare it with traditional machine learning and individual CNN and LSTM algorithms. Experimental results demonstrate significant performance improvements of our hybrid model in rehabilitation gesture recognition tasks, indicating promising application prospects and practical significance. © 2024 IEEE.

关键词： Convolutional neural networks

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Dual-modal Motion of Magnetically Controlled Soft Microrobots with Environmentally Responsive Reversible Deformation 24

Dual-modal Motion of Magnetically Controlled Soft Microrobot...

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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Xin, Zhengyuan Wu, Anping Bai, Kailun Yang, Haotian Lin, Kaijun Shi, Qing Wang, Huaping Hou, Yaozhen Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Science and Technology on Space Physics Laboratory Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9798400710681

Soft microrobots have garnered attention in the biomedical field due to their ability to access hard-to-reach regions within living organisms for precise manipulation. However, the inability to alter the stable morphology after design and fabrication remains a pressing issue for existing soft microrobots. This limitation results in a fixed range of locomotion modes, thereby restricting the diversity of operational environments. Addressing this challenge, this study proposes and designs a biocompatible X-shaped soft microrobot that achieves alterable stable morphologies through an innovative mechanism. We developed a deformable soft hydrogel robot based on alginate gel’s ability to reversibly swell in response to ion concentration changes. Based on the deformation characteristics of this microrobot, we have designed undulating and rolling locomotion modes that are suitable for different morphologies, along with their corresponding magnetic field manipulation systems, enabling multi-morphology locomotion of the robot. Experimental validations demonstrate that the designed flexible microrobot can achieve a deformation deflection angle of up to 150° under manipulation. This robot not only performs forward undulating locomotion in its expanded state but also executes rolling motion in its spherical configuration, exhibiting high locomotion flexibility and adaptability. © 2024 Copyright held by the owner/author(s).

关键词： Microrobots

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