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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Dai, Shijie Wu, Zhengxing Tan, Min Yu, Junzhi School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9789811966125

This paper investigates the formation control problem for a multi-robotic fish system and a distributed event-triggered-based formation control framework is proposed. The framework consists of a communication topology, a distributed formation control law, and a dynamic event-triggered communication mechanism. In particular, a position-based formation control law is presented to drive the multi-robotic fish system to an anticipated configuration based on local measurements while keeping pace with a moving target. Meanwhile, a dynamic event-triggered mechanism is utilized to measure importance of the interactive information and decide the communication timing. The proposed formation control method shows its merits to greatly reduce communication consumption with a limited loss of formation control performance. Finally, simulations with quantitative comparisons are presented to verify the effectiveness of the proposed framework. This formation control framework provides a solid foundation for future marine cooperative control of the multi-robotic fish system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Towards Autonomous Robotic Ultrasound Scanning Using the Reinforcement Learning-Based Volumetric Data Navigation Method 5

Towards Autonomous Robotic Ultrasound Scanning Using the Rei...

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5th World Robot Conference Symposium on Advanced robotics and Automation, WRC SARA 2023

作者： Shen, Cuifeng Deng, Zhaokun Wang, Jinzhi Wang, Shuangyi Chen, Chen Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Beijing100871 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong

ISBN: (纸本)9798350307320

Ultrasound scanning is an indispensable diagnostic tool in modern medicine, but obtaining an accurate standard plane relies heavily on the sonographer's skill and expertise. This paper presents a novel approach toward autonomous robotic ultrasound scanning using a reinforcement learning-based navigation method with volumetric ultrasound data. The proposed method enables an ultrasound robot to autonomously acquire high-quality 2D standard planes from patients, thereby reducing the need for human intervention. The core of the approach is a deep reinforcement learning algorithm that detects 2D standard planes within the 3D ultrasound volume and guides the ultrasound probe to extract high-quality standard planes. To assess the effectiveness of the 2D standard plane detection method, an evaluation was conducted using a realworld ultrasound dataset, and a comparison was made between its performance and that of other state-of-the-art autonomous approaches. The simulation experiment was also conducted to validate the autonomous robotic ultrasound acquisition workflow. Results demonstrate that the reinforcement learning-based volumetric data navigation method outperforms existing techniques in terms of standard plane accuracy and is very effective for volumetric data-based robotic navigation. © 2023 IEEE.

关键词： Diagnosis

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Model-Based Shape Estimation and Closed-Loop Control of Magnetic Continuum Robot Based on Monocular Vision

Model-Based Shape Estimation and Closed-Loop Control of Magn...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhu, Junfeng Huang, Yuanrui Chen, Jian Liu, Hongbin School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100049 China Hong Kong Institute of Science Innovation Chinese Academy of Sciences Centre of AI and Robotics China School of Biomedical Engineering and Imaging Sciences King's College London United Kingdom

ISBN: (纸本)9781665481090

Magnetic continuum robots (MCRs) show promising potential for applications in narrow lumens, such as vascular interventions. Accurate shape sensing of these robots is crucial for the success of interventional surgeries. However, the submillimeter dimensions of MCRs poses significant challenges for integrating additional sensors. An alternative approach is shape estimation from images, yet the lack of precise MCR kinematics can make this process time-consuming. In this work, we propose a novel MCR design featuring a rectangular tip capable of specific planar bending, along with a corresponding kinematic model and a mechanical model. Additionally, we introduce a model-based shape estimation method that enables the estimation of the MCR's shape from a single-view image without the need for external markers. Experimental results demonstrate that our method can estimate an MCR's shape with a mean absolute error (MAE) of 0.58 ± 0.41 mm within 85ms, facilitating real-time application. Furthermore, closed-loop control based on this method has achieved an end position error below 11% of the tip's total length, highlighting the accuracy and practicality of our approach for surgical interventions. © 2024 IEEE.

关键词： Closed loop control systems

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Unsupervised Cross-Domain 3D Human Pose Estimation via Pseudo-Label-Guided Global Transforms

arXiv

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arXiv 2025年

作者： Liu, Jingjing Wang, Zhiyong Fan, Xinyu Dadashzadeh, Amirhossein Liu, Honghai Mirmehdi, Majid School of Computer Science University of Bristol United Kingdom State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen China School of Aerospace Engineering Xiamen University China

Existing 3D human pose estimation methods often suffer in performance, when applied to cross-scenario inference, due to domain shifts in characteristics such as camera viewpoint, position, posture, and body size. Among these factors, camera viewpoints and locations have been shown to contribute significantly to the domain gap by influencing the global positions of human poses. To address this, we propose a novel framework that explicitly conducts global transformations between pose positions in the camera coordinate systems of source and target domains. We start with a Pseudo-Label Generation Module that is applied to the 2D poses of the target dataset to generate pseudo-3D poses. Then, a Global Transformation Module leverages a human-centered coordinate system as a novel bridging mechanism to seamlessly align the positional orientations of poses across disparate domains, ensuring consistent spatial referencing. To further enhance generalization, a Pose Augmentor is incorporated to address variations in human posture and body size. This process is iterative, allowing refined pseudo-labels to progressively improve guidance for domain adaptation. Our method is evaluated on various cross-dataset benchmarks, including Human3.6M, MPI-INF-3DHP, and 3DPW. The proposed method outperforms state-of-the-art approaches and even outperforms the target-trained model. Copyright © 2025, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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A New Workspace and Structural Parameter Optimization Method of Parallel Robot 18

A New Workspace and Structural Parameter Optimization Method...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhang, Haiyun Hu, Weijun Zhang, Renge Wang, Jin Lu, Guodong School of Robotics Ningbo University of Technology Ningbo315211 China Robotics Institute of Zhejiang University Hangzhou310027 China Zhejiang Qiantang Robot and Intelligent Equipment Reserch Co. Ltd Hangzhou310018 China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China

ISBN: (纸本)9798350312201

The parallel robot workspace refers to the set of points and boundary that can be reached by the parallel mechanism. With the continuous development and industrial application of parallel robots, the workspace analysis and optimization becomes a critical link in this process. In this paper, a workspace solution approach based on seed space segmentation and principal component analysis is proposed. In order to improve the working performance of parallel robots, a flexible workspace evaluation method based on quadratic fourth moment is proposed, and a relationship model between flexible workspace and structural parameters is established. Furthermore, based on the multi-objective genetic algorithm, the structure parameters of the parallel robot are optimized by the workspace and flexible workspace indexes. Finally, the advantage and effectiveness of proposed method are verified by experiment and comparison with traditional methods. © 2023 IEEE.

关键词： Principal component analysis

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A kinematic calibration method for robots based on the PGTF error model and Levenberg-Marquardt algorithm 18

A kinematic calibration method for robots based on the PGTF ...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zheng, Zhi Wang, Jin Zhu, Jun Liu, Luan Zhang, Haiyun Lu, Guodong State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China School of Robotics Ningbo University of Technology Ningbo315211 China Robotics Institute of Zhejiang University Hangzhou310027 China Zhejiang Qiantang Robot and Intelligent Equipment Research Co. Ltd Hangzhou310018 China

ISBN: (纸本)9798350312201

Robots use motors for power output and realize joint motion through reducers and mechanical transmissions, which affect the absolute positioning accuracy. In view of this problem, an error model based on Preprocessing-Geometric-Transmission-Flexibility (PGTF) is proposed and solved by Levenberg-Marquardt algorithm. First, the theoretical kinematic model is established by MD-H model method. Second, the data was pre-processed in dimension upgrade and the robot error identification model was established for geometric error, transmission error and flexible error. Third, Levenberg-Marquardt algorithm was used to find the global convergence solution to realize the identification of error parameters, and the actual robot kinematic model was compensated. Finally, the experiment is carried out on the real robot machine. Through theoretical analysis and verification of real machine data, the average error of kenbei-5kg robot is reduced from 6.8787 mm to 0.1267 mm, the positioning accuracy is improved by 98.16%, the accuracy compensation algorithm is accurate, and the compensation effect is remarkable. © 2023 IEEE.

关键词： Robots

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CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face Anti-Spoofing 18

CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face A...

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18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Zhang, Ying Zhu, Xiangyu Liu, Ajian Lin, Xun Wan, Jun Zhang, Jing Lei, Zhen Beihang University School of Computer Science and Engineering China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation China University of Chinese Academy of Sciences School of Artificial Intelligence China Macau University of Science and Technology School of Computer Science and Engineering China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation China

ISBN: (纸本)9798350364132

Face anti-spoofing (FAS) is pivotal in safeguarding the integrity of face recognition systems. Flexible-modal FAS utilizes multi-modal data and trains a unified model adaptable to any single-modal testing scenario. This innovation addresses the shortcomings of conventional multi-modal FAS approaches, which typically demand separate model training and deployment for each modality. However, existing flexible-modal FAS approaches activate specific network branches based on the modality of the tested sample. This not only increases the model's parameters but also necessitates the provision of the image's modality for testing, thereby constraining deployment flexibility. To address the issue, we present Compound Prompt Learning CLIP (CPL-CLIP), a novel method for flexible-modal FAS. This approach capitalizes on a learned textual prompt that is nearly independent of modality, thus bolstering class-based classification across arbitrary modalities. Specifically, our CPL-CLIP introduces a Dual-Branch Prompt (DBP), consisting of class and modal prompts that describe and guide classification, where each prompt is composed of learnable vectors and fixed templates. To further render the class prompt as modality-agnostic as possible, a Cosine Similarity Loss (CSL) is proposed to facilitate the maximal separation of the class prompt from the modality prompt. With only the class prompt utilized during testing, CPL-CLIP enables deployment in diverse modal testing scenarios without the necessity of the test image's modality to be known. Extensive experiments demonstrate CPL-CLIP's superiority over existing methods on several flexible-modal FAS benchmarks. © 2024 IEEE.

关键词： Face recognition

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Dynamic Identification for a Manipulator Model based on Stribeck Friction using the Quasi-Newton Iterative Method

Dynamic Identification for a Manipulator Model based on Stri...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xiao, Feng Zhang, Feilong Han, Bing Zhang, Hualiang Shenyang University of Technology School of Information Science and Engineering Shenyang110870 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China School of Mechanical Engineering Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China

ISBN: (纸本)9798350325706

The performance of dynamic control is intimately tied to modeling accuracy. However, traditional estimation methods and friction models, such as the least squares method and the Coulomb plus viscous model, fail to reflect the actual characteristics accurately. Particularly, the linear nature of the Coulomb plus viscous model overlooks the nonlinear static features of joint friction at slower velocities. To improve the rationality of the model structure, we integrate the Stribeck friction model into the Coulomb plus viscous model. However, introducing such nonlinearities compromises the applicability of the least squares method. As a countermeasure, we propose a new strategy that combines the least square method and the Quasi-Newton iterative method to identify the parameters of the modified nonlinear model. Additionally, the design of the excitation trajectory is critical to achieve high identification accuracy. We utilized the inverse of the smallest singular value of the observation matrix as the objective function. By minimizing it with the interior point method, we generate the excitation trajectory well-suited to stimulate dynamic characteristics. Then we leverage the discrepancies between the measured and estimated torques to assess the precision of the dynamic parameters of the manipulator. Remarkably, our proposed algorithm reduces the mean absolute error of the estimated torque by over 20.40%. Finally, an experiment of the industrial manipulator by hand guiding grab and drag is performed and shows that the proposed approach can provide the manipulator with comprehensive torque compensation. © 2023 IEEE.

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A Portable and Integrated Traveling-Wave Electroosmosis Microfluidic Pumping System Driven by Triboelectric Nanogenerator

SSRN

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SSRN 2024年

作者： Zhou, Jian Tao, Ye Liu, Weiyu Sun, Tie Wu, Fangyu Shi, Changrui Ren, Yukun State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China School of Electronics and Control Engineering Chang'an University Xi’an710064 China

The lab-on-a-chip system can simultaneously complete the preparation, reaction, separation, and detection of samples on a centi-scale platform by manipulating trace fluids. Traveling-wave electroosmosis (TWEO) technology, with the merit of electric signal-based flexible control over the fluid behavior, can achieve precise driving of fluids, which is an important requirement of the lab-on-a-chip system. However, the peripheral power equipment such as function generator required for TWEO limits the application in some occasions lacking power supply facilities, due to its large size and high cost. In this paper, we developed a brand-new portable and integrated TWEO microfluidic pumping system, wherein a front-end module of triboelectric nanogenerator (TENG) is in serial connection with the back-end microfluidic pumping chip, which greatly improves portability and reduces costs. The TENG can output a stable four consecutively 90°-phase-shifted alternating current voltage signals in a continuous rotational motion originated by its novel electrode structure. And the four-phase traveling potential waves are applied to four sets of electrode strips alternately distributed in the microchannel and thereby induce nonlinear electroosmotic slip on the electrode surface. Compared with traditional mechanical pumps, this system achieves stable pumping of electrolyte in the microchannel, but also realizes the almost instantaneous start, stop, and directional switching in response to a turn on, turn off, and turn in reverse of TENG, respectively. Finally, this system is integrated into a droplet microfluidic chip for the efficient fabrication of single emulsion droplets. This study presents a promising solution for the miniaturization, integration, and commercialization of lab-on-a-chip system. © 2024, The Authors. All rights reserved.

关键词： Lab-on-a-chip

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NA-CPG: A robust and stable rhythm generator for robot motion control

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Biomimetic Intelligence & robotics 2022年第4期2卷 30-38页

作者： Ru Tong Changlin Qiu Zhengxing Wu Jian Wang Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic ***,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological ***,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot ***,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are ***-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output ***,it can effectively cope with large parameter changes to avoid network oscillations and *** optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further ***,a biomimetic robotic fish is illustrated to realize the whole optimization *** demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,*** proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

关键词： Normalized asymmetric CPGs Rhythm generator Motion control Robotic fish

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