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International Conference on Control, Automation and systems ( ICCAS)

作者： Jae Hoon Son Yeong Hye Lee Junwoo Jurug Yongtaek Hwang Jiwoo Hwang Minsu Kim Gyeongmin Park JunMin Park Hoyoung Yoo Chansik Park Sang Heon Oh Sang Jeong Lee Dong-Hwan Hwang Department of Electronics Engineering Chungnam National University Daejeon Korea Department of Intelligent Systems & Robotics Chungbuk National University Daejeon Korea Advanced Technology Laboratory Microinfinity Co. Ltd. Daejeon Korea

When a navigation systems are developed, lots of tests have to be performed. If a simulator is available which can generate signal and data of real environment, huge amount of time and cost can be reduced for development. In this paper, a simulator design method is proposed for GNSS/INS integrated navigation system using a general-purpose PC and OTS interface boards. In order to verify the proposed design method, a simulator of GPS L1 C/A and HG1700AG58 is implemented using a PC with intel i7-8700 CPU, USRP 2952-R, PCI-1780U-AE, FSCC/4-PCIe and LabVIEW2015. The implementation results show that GNSS signal and IMU data can be used for GNSS/INS integrated navigation system design.

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TactCapsNet: Tactile capsule network for object hardness recognition

TactCapsNet: Tactile capsule network for object hardness rec...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Fang, Senlin Mi, Tingting Zhou, Zhenning Ye, Chaoxiang Liu, Chengliang Wu, Hancheng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9781665436786

Hardness is one of the most essential tactile clues for robots to recognize objects. However, methods for robots to recognize hardness are limited. In this paper, based on the Capsule Network (CapsNet), we propose a novel tactile capsule network (TactCapsNet) for object hardness recognition. Specifically, we collect a tactile dataset on the silicone samples with three different shapes, and the silicone samples of each shape have thirteen hardness levels ranging from 0A (Shore A scale) to 60A at 5A intervals. Furthermore, we construct the tactile image as the input of the CapsNet to make full use of the spatio-temporal information of the tactile hardness dataset. The experimental results prove that the proposed approach achieves higher accuracy and quadratic weighted kappa (QWK) than support vector machine (SVM), long short-term memory (LSTM), convolutional neural network (CNN), and CapsNet. © 2021 IEEE.

关键词： Hardness

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Hydrogel-elastomer-based stretchable strain sensor fabricated by a simple projection lithography method

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International Journal of Smart and Nano Materials 2021年第3期12卷 256-268页

作者： Zhenqing Li Xiangnan He Jianxiang Cheng Honggeng Li Yuan-Fang Zhang Xiaojuan Shi Kai Yu Hui Ying Yang Qi Ge Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhenChina Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and TechnologyShenzhenChina Digital Manufacturing and Design Centre Singapore University of Technology and DesignSingapore Department of Mechanical Engineering University of Colorado DenverDenverCOUSA National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbinP.R.China

Stretchable strain sensor detects a wide range of strain variation and is therefore a key component in various *** traditional ones made of elastomers doped with conductive components or fabricated with liquid conductors,ionically conductive hydrogel-based strain sensors remain conductive under large deformations and are ***,dehydration is a challenging issue for the *** have developed hydrogel-elastomer-based strain sensors where an elastomer matrix encapsulates a hydrogel circuit to prevent its ***,the reported multistep approaches are generally *** group recently reported a multimaterial 3D printing approach that enables fast fabrication of such sensors,yet requires a self-built digital-light-processing-based multimaterial 3D ***,we report a simple projection lithography method to fabricate hydrogel-elastomer-based stretchable strain sensors within 5 *** method only requires a UV projector/lamp with photomasks;the chemicals are commercially available;the protocols for preparing the polymer precursors are friendly to users without chemistry ***,the manufacturing flexibility allows users to readily pattern the sensor circuit and attach the sensor to a 3D printed soft pneumatic actuator to enable strain sensing on the *** proposed approach paves a simple and versatile way to fabricate hydrogel-elastomer-based stretchable strain sensors and flexible electronic devices.

关键词： Ionically conductive hydrogel stretchable strain sensor projection lithography

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Exoskeleton-Based Lower Limb Rehabilitation Robot Design and Simulation for Children with Cerebral Palsy

Exoskeleton-Based Lower Limb Rehabilitation Robot Design and...

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World Rehabilitation Robot Convention (WRRC)

作者： Wujing Cao Shuo Zhang Yupeng Zou Xinqiang Guo Changyu Li Jingxin Wang Worawarit Kobsiriphat Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China and SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems. SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society School of Mechanical Engineering China University of Petroleum East China Jining Zhongke Intelligent Technology Co. Ltd. Department of Rehabilitation Medicine Zhengzhou Central Hospital Affiliated Zhengzhou University Zhengzhou China National Metal and Materials Technology Center Thailand

ISBN: (数字)9798350355123

ISBN: (纸本)9798350355130

Squat gait is the most common abnormal gait in children with cerebral palsy. Gait training with lower limb rehabilitation robots can improve rehabilitation efficiency and reduce manual labor for them. A novel exoskeleton-based lower limb rehabilitation robot for children with cerebral palsy is proposed, considering the squat gait characteristics of children with cerebral palsy. The structure of the lower limb rehabilitation robot, which combines hip and knee with 4 active degrees of freedom exoskeleton and mobile walker, is designed and optimized. Static analysis of the key mechanical structure of the exoskeleton is conducted using ANSYS Workbench, and local structures are optimized to ensure the safety factor of the mechanical structure is greater than 1, guaranteeing reasonable structural strength and stiffness design. Dynamic simulation analysis based on the ADAMS model validates the reliability and dynamic walking effect of the lower limb exoskeleton rehabilitation robot, obtaining the curve relationship between joint angles and motion cycles, thus verifying the effectiveness of the mechanical system motion.

关键词： Knee Training Cerebral palsy Exoskeletons Dynamics Static analysis Assistive robots Safety Finite element analysis Hip

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Mathematical Modelling of a Four-Fingered Metamorphic Anthropomorphic Hand on Precision Grasp

Mathematical Modelling of a Four-Fingered Metamorphic Anthro...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Tun Wang Yen-Hua Lin Jian S. Dai Department of Mechanical and Electrical Engineering Centre of Advanced Oil and Gas Equipment China University of Petroleum (Beijing) Beijing China Department of Engineering Centre for Robotics Research King's College London London UK Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

For a metamorphic robotic hand with a foldable palm, its finger operation planes change with palm configurations. Although this reconfigurable design can enhance the grasp flexibility, manipulation workspace and application adaptability, the hand's grasp stability cannot be guaranteed when the palm reconfigures. Especially for the four-fingered metamorphic hand performing precision grasps in anthropomorphic postures, improper control of the palm configurations can result in unsuccessful grasps, which may even lead to hand damage. This paper first displays the workspace of the four-fingered anthropomorphic hand for generating precision grasp gestures. Based on it, force-closure/-balance analyses are performed, deriving the effective precision grasp workspace for typical anthropomorphic postures classified by built mathematical definition. Grasp levels are further discussed by introducing an evaluation method which considers the minimum friction coefficient (MFC) as the quality metric. The proposed scheme gives a way to depict the grasp performance of every robotic hand configuration, without considering specific objects that are to be grasped. Dynamic changes in postures' grasp performance with palm configurations are exhibited in the end.

关键词： Measurement Friction Mathematical models Stability analysis Robots Petroleum

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基于自解耦三明治结构的横向运动栅场效应晶体管MEMS微力传感器

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Engineering 2023年第2期21卷 61-74,M0004页

作者：高文迪乔智霞韩香广王小章 Adnan Shakoor 刘存朗卢德江杨萍赵立波王永录王久洪蒋庄德孙东 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 265503China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150006China Eleventh Research Institute Sixth Academy of China Aerospace Science and Technology Co.Xi’an 710100China Department of Control and Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Biomedical Engineering City University of Hong KongHong Kong 999077China

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵... 详细信息

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵列层和两个软光阻层SU-8组成。通过所提出的双差分传感结构,LMGFET横向工作在垂直干扰下的输出电流被大大消除,所提出传感器的相对输出误差从4.53%(传统差分结构)降低到0.01%。提出了一种实用的传感器制造工艺,并对其进行了模拟。基于LMGFET的力传感器的灵敏度为4.65μA·nN^(-1),可与垂直可移动栅极场效应晶体管(VMGFET)器件相媲美,但非线性度提高了0.78%,测量范围扩大了±5.10μN。这些分析为LMGFET器件的电气和结构参数提供了全面的设计优化,并证明了所提出的传感器在生物医学显微操作应用中具有良好的力传感潜力。

关键词：力传感器场效应晶体管横向运动三明治结构电气模型显微操作非线性度双差分

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Lateral Walking Gait Phase Detection with Data Optimization for a Hip Exoskeleton in Resistance Exercise

Lateral Walking Gait Phase Detection with Data Optimization ...

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IEEE Workshop on advanced robotics and its Social Impacts, ARSO

作者： Wujing Cao Xinbo Zhu Rui Xu Changyu Li Hongliu Yu Mingming Zhang Haoyong Yu Worawarit Kobsiriphat Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society and SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems. College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jining Zhongke Intelligent Technology Co. Ltd. University of Shanghai for Science and Technology Southern University of Science and Technology Department of Biomedical Engineering National University of Singapore. National Metal and Materials Technology Center Thailand

ISBN: (数字)9798350344639

ISBN: (纸本)9798350344646

The accurate detection of lateral walking gait phases is essential for the effective implementation of hip exoskeleton systems in lateral resistance walking exercises. However, limitations in hardware, such as memory and computing power, in the microcontrollers of wearable devices, significantly impact the size and training speed of the lateral walking gait phase detection model, thus affecting the exoskeleton system. This study proposes a data optimization algorithm that utilizes K-means clustering combined with commonly used machine learning algorithms, including Random Forests (RF), Support Vector Machines (SVM), and k-Nearest Neighbors (KNN), to reduce both the training time and size of the model. With the implementation of this algorithm, the training time and model size of RF, SVM, and KNN-based models are reduced by 89.6%, 99.8%, and 97.9%, and 89.6%, 92.7%, and 95.2% respectively. The corresponding gait phase prediction accuracy experiences only a slight decrease of 1.6%, 1.7%, and 2.8% respectively. This method ensures a sufficiently high accuracy in detecting lateral walking gait phases while simultaneously achieving higher efficiency and a smaller model size.

关键词： Legged locomotion Training Support vector machines Solid modeling Machine learning algorithms Accuracy Exoskeletons

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Design and Simulation of a Helical Microrobot for Maximum Speed Enhancement by Physical Surface Modification

Design and Simulation of a Helical Microrobot for Maximum Sp...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Siyu Guo Maolin Wang Huaping Wang Shihao Zhong Yukang Qiu Yaozhen Hou Qing Shi Toshio Fukuda School of Mechatronical Engineering Intelligent Robotics Institute Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Magnetic helical microrobots have great potential in biomedical applications. However, improving their motion performance in the complex and variable in vivo fluid environment remains challenging. Previous researches mainly focus on optimizing the geometric parameter, the evolutionary structure design, and chemical modifications of the robots, with limited attention given to the impact of physical surface modifications on propulsion performance. To address this issue, we design the helical microrobot with different surface physical modifications, including dimpled and raised surfaces, to evaluate their effects on swimming performance. With ANSYS Fluent, we simulated their swimming process in water and found that microrobots with physically modified surfaces experience less resistance and exhibit a larger step-out frequency while swimming. Moreover, our findings suggest that helical microrobots with dimpled surfaces demonstrate superior swimming performance due to their larger gas-liquid interface area compared to those with raised surfaces.

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Modeling Neural Representation of Social Recognition Information with Recurrent Neural Networks 17

Modeling Neural Representation of Social Recognition Informa...

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17th International Conference on Complex Medical Engineering, CME 2023

作者： Song, Fei Wang, Xinnian Zhan, Yang Tang, Fengzhen Si, Bailu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China School of Life Sciences Division of Life Science and Medicine University of Science and Technology of China Hefei230026 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Systems Science Beijing Normal University Beijing100091 China Chinese Institute for Brain Research Beijing102206 China

ISBN: (纸本)9798350316117

Social recognition, the ability to differentiate between familiar and unfamiliar individuals, is crucial for animals' survival and reproduction. Neuroscience research has predominantly focused on investigating the brain regions and circuits that regulate social recognition. However, a lingering question pertains to the precise mechanisms underlying the social recognition process. To address this question, we employed a recurrent neural network (RNN) to determine whether an agent can recognize familiar individuals without involving higher-level decision-making processes. This approach takes into consideration that animal behavioral performance may not directly mirror complex cognitive functions. The RNN was trained using the full-FORCE learning paradigm. Our simulation results revealed three distinct subsets of neurons with specific functions: one dedicated to representing novel individuals and two others representing the same social individual in both unfamiliar and familiar states. We propose a hypothesis regarding the potential memory computing processes involved in these operations. © 2023 IEEE.

关键词： Animals

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Path Tracking Control for Helical Microrobots Based on Fusion of Geometric and Model-Free Methods

Path Tracking Control for Helical Microrobots Based on Fusio...

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IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems

作者： Shihao Zhong Huaping Wang Qing Shi Yaozhen Hou Yukang Qiu Tao Sun Qiang Huang Toshio Fukuda School of Medical Technology Beijing Institute of Technology Beijing China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

Helical micron-sized robots driven by magnetic fields have garnered significant interest, particularly in the field of tracking control. However, at the microscale, time-varying uncertain perturbations in both the environment and electromagnetic system can cause these robots to deviate from their preset state. Here, we propose a novel control method that combines geometric and model-free controllers in a complementary manner to achieve accurate path-tracking of a helical microrobot on underwater unstructured surfaces. The geometric controller acts as a feedforward controller handling path information and formulating guidance law, while the model-free controller responds directly to the lateral error. To compensate for unmodeled nonlinear dynamics and unknown disturbances and achieve system dynamic linearization, we employ an extended state observer. To validate the proposed method and determine suitable ranges for input parameters of the controllers, simulations were carried out. The effectiveness of our path-tracking control method is validated through experimental results. The control technique provides an initial investigation into addressing the effects of uncertainties and perturbation on the control capabilities of magnetic microrobots.

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