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IEEE International Conference on robotics and Biomimetics

作者： Zhihui Xu Tanyong Wei Zongze Li Ding Huang Shoubin Liu Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

Capsule robots have emerged as a promising solution for non-invasive and painless screening of gastrointestinal diseases, offering significant advantages in patient comfort and reduced risk of cross-infection. Despite these advantages, existing capsule robots fall short in their ability to conduct targeted biopsies and deliver drugs to specific gastric lesions. To address this limitation, this paper presents the design and development of a magnetically driven capsule robot that leverages visual feedback to achieve accurate targeting for biopsy and drug administration in gastric lesions. Internal magnets, responsive to an external gradient magnetic field, enable the controlled propulsion of the capsule robot. A kinetic model of the capsule robot is analyzed, allowing it to recognize lesion contours through the endoscopic camera. This recognition determines the rotation angle or small adjustments required for the capsule robot's attitude and positioning. Experimental results in a simplified in vitro stomach model showcase the capability of the capsule robot to achieve targeted biopsy and drug delivery. These results highlight the potential feasibility of the proposed capsule robot in enhancing diagnostic accuracy and treatment efficacy with broader applications within the realm of gastric healthcare.

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Identification of PMSM Moment of Inertia based on Model Reference Adaptive Algorithm 4

Identification of PMSM Moment of Inertia based on Model Refe...

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4th IEEE International Conference on Power, Intelligent Computing and systems, ICPICS 2022

作者： Ding, Fan Zhang, Tao Jia, Danping Zhang, Hualiang Pei, Quanshen Huang, Haoran School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

A method that can identify the rotational inertia in a timely manner is proposed because the performance of a permanent magnet synchronous motor servo system is easily affected by the rotational inertia. Firstly, principles of model-referenced adaptive recognition algorithm is introduced, and the influence of the adaptive gain on the identification results is analyzed. Then, design a suitable range of adaptive gain value, use the set error value to compare the identification error with the set value, and then select the appropriate gain for identification. Finally, through simulation verification, this method has fast identification convergence speed, high precision and strong anti-disturbance. © 2022 IEEE.

关键词： Adaptive algorithms

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A Learning Quasi-stiffness Control Framework of a Powered Transfemoral Prosthesis for Adaptive Speed and Incline Walking

arXiv

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arXiv 2023年

作者： Ma, Teng Yin, Shucong Hou, Zhimin Wang, Yuxuan Huang, Binxin Yu, Haoyong Fu, Chenglong Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Department of Biomedical Engineering National University of Singapore Singapore119077 Singapore

Impedance-based control represents a prevalent strategy in the powered transfemoral prostheses because of its ability to reproduce natural walking. However, most existing studies have developed impedance-based prosthesis controllers for specific tasks, while creating a task-adaptive controller for variable-task walking continues to be a significant challenge. This article proposes a task-adaptive quasi-stiffness control framework for powered prostheses that generalizes across various walking tasks, including the torque-angle relationship reconstruction part and the quasi-stiffness controller design part. A Gaussian Process Regression (GPR) model is introduced to predict the target features of the human joint’s angle and torque in a new task. Subsequently, a Kernelized Movement Primitives (KMP) is employed to reconstruct the torque-angle relationship of the new task from multiple human reference trajectories and estimated target features. Based on the torque-angle relationship of the new task, a quasi-stiffness control approach is designed for a powered prosthesis. Finally, the proposed framework is validated through practical examples, including varying speeds and inclines walking tasks. Notably, the proposed framework not only aligns with but frequently surpasses the performance of a benchmark finite state machine impedance controller (FSMIC) without necessitating manual impedance tuning and has the potential to expand to variable walking tasks in daily life for the transfemoral amputees. © 2023, CC BY.

关键词： Adaptive control systems

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Brain Rhythmic Activity and Hemodynamic Response During Wrist Extension Induced by Functional Electrical Stimulation 17

Brain Rhythmic Activity and Hemodynamic Response During Wris...

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17th International Convention on Rehabilitation engineering and Assistive Technology, i-CREATe 2024

作者： Mao, He Peng, Yinghu Zheng, Yue Li, Guanglin Li, Hai Xu, Yongan Fang, Peng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen518055 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen518055 China Southern Medical University Neurorehabilitation Laboratory Department of Rehabilitation Medicine Shenzhen Hospital Shenzhen518101 China Second Affiliated Hospital Institute of Emergency Medicine Zhejiang University School of Medicine Department of Emergency Medicine Hangzhou310009 China

ISBN: (纸本)9798350355154

Functional electrical stimulation (FES) is an effective therapy for motor function restoration after stroke. To investigate brain activation during FES-induced wrist extension, electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) were simultaneously measured for 6 healthy subjects. We found an increase in oxygenated hemoglobin (HbO) concentration, which was accompanied by a decrease in deoxygenated hemoglobin (HbR) concentration in bilateral sensorimotor cortex (SMC) during movement. We also found event-related desynchronization (ERD) of alpha and beta EEG rhythms during movement and event-related synchronization (ERS) after the cessation of the movement. Neurovascular coupling (NC) was evaluated by the correlation coefficient (cc) between alpha ERD and HbO, and a higher cc value was found on the contralateral hemisphere. These findings demonstrate the potential application of EEG-fNIRS for quantifying NC during FES therapy. © 2024 IEEE.

关键词： Electroencephalography

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Adaptive RBF-Neural-Network Control with Force Observer for Teleoperation Robotic System 1st

Adaptive RBF-Neural-Network Control with Force Observer for...

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1st International Conference on Cognitive Computation and systems, ICCCS 2022

作者： An, Zhaohui Min, Gaochen Jiang, Xiangzuo Yu, Xinbo He, Wei Silvestre, Carlos School of Intelligence Science and Technology Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing100083 China Donald Bren School of Information and Computer Sciences University of California IrvineCA92697 United States Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China LARSyS Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (纸本)9789819927883

In this paper, an adaptive radial basis function neural network (RBFNN) control strategy is proposed for bilateral teleoperation robotic system with uncertainty and time delay. Meantime, the force observer method is used to estimate the interaction force between the slave robot and environment. The model of teleoperation robotic system is analyzed, and then the uncertainty of bilateral teleoperation robotic system is estimated by using RBFNN. Using Lyapunov stability theorem, the stability of teleoperation robotic system under our proposed control is proved. Finally, the effectiveness of the proposed control algorithm is verified by Matlab Simulink, and position tracking and force estimation performance of the teleoperation robotic system are guaranteed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time delay

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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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Object Detection Methods for a Robot Soccer

Object Detection Methods for a Robot Soccer

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Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Ramir Sultanov Roman Lavrenov Shifa Sulaiman Yang Bai Mikhail Svinin Evgeni Magid Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Information Science and Engineering Department Ritsumeikan University Biwako-Kusatsu Campus Shiga Japan

Soccer tournaments between robot teams are being held around the world to encourage robotic research. An accurate detection and tracking of a ball position, an identification of robots and objects during a game are crucial for robot teams. In this paper, object detection methods for identifying robots and a ball during a robot soccer game are presented. Standard OpenCV library functions were adjusted for a ball and robots' detection. Simulation studies were carried out in Gazebo environment to compare a performance of various methods discussed in this paper.

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Data-based Stabilization of Unknown Discrete-time 2-D Roesser systems

Data-based Stabilization of Unknown Discrete-time 2-D Roesse...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Runmin Yang Rongni Yang Renjie Ma Yanzheng Zhu Peng Shi School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China School of Electrical and Mechanical Engineering University of Adelaide Adelaide SA Australia

ISBN: (数字)9798331528041

ISBN: (纸本)9798331528058

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

关键词： Sufficient conditions State feedback Two-dimensional displays Transforms Machine learning Stability analysis Data models Numerical models Closed loop systems Numerical stability

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D2NT: A High-Performing Depth-to-Normal Translator

D2NT: A High-Performing Depth-to-Normal Translator

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yi Feng Bohuan Xue Ming Liu Qijun Chen Rui Fan Robotics & Artificial Intelligence Laboratory (RAIL) the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems the College of Electronic & Information Engineering Tongji University Shanghai P. R. China Department of Computer Science & Engineering the Hong Kong University of Science and Technology (Guangzhou) Hong Kong SAR P. R. China Robotics & Autonomous Systems Thrust of the Systems Hub the Hong Kong University of Science and Technol-ogy (Guangzhou) Nansha Guangzhou P. R. China

Surface normal holds significant importance in visual environmental perception, serving as a source of rich geometric information. However, the state-of-the-art (SoTA) surface normal estimators (SNEs) generally suffer from an unsatisfactory trade-off between efficiency and accuracy. To resolve this dilemma, this paper first presents a superfast depth-to-normal translator (D2NT), which can directly translate depth images into surface normal maps without calculating 3D coordinates. We then propose a discontinuity-aware gradient (DAG) filter, which adaptively generates gradient convolution kernels to improve depth gradient estimation. Finally, we propose a surface normal refinement module that can easily be integrated into any depth-to-normal SNEs, substantially improving the surface normal estimation accuracy. Our proposed algorithm demonstrates the best accuracy among all other existing real-time SNEs and achieves the SoTA trade-off between efficiency and accuracy.

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Thermal Casting for Monolithic Soft Actuators

Thermal Casting for Monolithic Soft Actuators

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IEEE International Conference on robotics and Biomimetics

作者： Huacen Wang Boyu Yang Junling Mei Yujin Dai Yixuan Xia Hongqiang Wang Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Department of Mechanical and Energy Engineering and Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) Guangzhou China

ISBN: (纸本)9781665481106

Soft robotics has significantly impacted many fields in the last decades. However, their current fabrication methodologies are limited by the assemble complexity, limited materials, or long duration. A monolithic thermal casting method for fabrication of elastomer and soft robotics based on thermoset polymer is introduced. In this work, we used simple heating cores to manufacture elastomers and soft actuators. By controlling the heating current and duration, we can adjust the thermal field and consequently change the configuration of the generated elastomer. Due to its short duration (several minutes), this method can benefit the mass production of soft robots for high efficiency. Also, this work offers a new way to design soft robotics without complex molds.

关键词： Fabrication Actuators Casting Spirals Wires Metals Soft robotics

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