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arXiv 2024年

作者： Bian, Shirui Wang, Zezhou Leng, Siyang Lin, Wei Shi, Jifan School of Mathematical Sciences Fudan University Shanghai200433 China Shanghai Center for Mathematical Sciences Fudan University Shanghai200433 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Institute of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai200433 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China State Key Laboratory of Medical Neurobiology MOE Frontiers Center for Brain Science Fudan University Shanghai200032 China

Early-warning signals of delicate design are always used to predict critical transitions in complex systems, which makes it possible to render the systems far away from the catastrophic state by introducing timely interventions. Traditional signals including the dynamical network biomarker (DNB), based on statistical properties such as variance and autocorrelation of nodal dynamics, overlook directional interactions and thus have limitations in capturing underlying mechanisms and simultaneously sustaining robustness against noise perturbations. This paper therefore introduces a framework of causal network markers (CNMs) by incorporating causality indicators, which reflect the directional influence between variables. Actually, to detect and identify the tipping points ahead of critical transition, two markers are designed: CNM-GC for linear causality and CNM-TE for non-linear causality, as well as a functional representation of different causality indicators and a clustering technique to verify the system’s dominant group. Through demonstrations using benchmark models and real-world datasets of epileptic seizure, the framework of CNMs shows higher predictive power and accuracy than the traditional DNB indicator. It is believed that, due to the versatility and scalability, the CNMs are suitable for comprehensively evaluating the systems. The most possible direction for application includes the identification of tipping points in clinical disease. Copyright © 2024, The Authors. All rights reserved.

关键词： Autocorrelation

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Observability Analysis of Graph SLAM-Based Joint Calibration of Multiple Microphone Arrays and Sound Source Localization

arXiv

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arXiv 2022年

作者： He, Yuanzheng Wang, Jiang Su, Daobilige Nakadai, Kazuhiro Wu, Junfeng Huang, Shoudong Li, Youfu Kong, He Shenzhen518055 China The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen518055 China College of Engineering China Agricultural University Beijing China The Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan The School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China The Robotics Institute University of Technology Sydney Sydney Australia The Department of Mechanical Engineering City University of Hong Kong Hong Kong

Multiple microphone arrays have many applications in robot audition, including sound source localization, audio scene perception and analysis, etc. However, accurate calibration of multiple microphone arrays remains a challenge because there are many unknown parameters to be identified, including the Euler angles, geometry, asynchronous factors between the microphone arrays. This paper is concerned with joint calibration of multiple microphone arrays and sound source localization using graph simultaneous localization and mapping (SLAM). By using a Fisher information matrix (FIM) approach, we focus on the observability analysis of the graph SLAM framework for the above-mentioned calibration problem. We thoroughly investigate the identifiability of the unknown parameters, including the Euler angles, geometry, asynchronous effects between the microphone arrays, and the sound source locations. We establish necessary/sufficient conditions under which the FIM and the Jacobian matrix have full column rank, which implies the identifiability of the unknown parameters. These conditions are closely related to the variation in the motion of the sound source and the configuration of microphone arrays, and have intuitive and physical interpretations. We also discover several scenarios where the unknown parameters are not uniquely identifiable. All theoretical findings are demonstrated using simulation data. © 2022, CC BY.

关键词： Microphone array

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A Toolkit to Generate Social Navigation Datasets 21st

A Toolkit to Generate Social Navigation Datasets

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21st International Workshop of Physical Agents, WAF 2020

作者： Baghel, Rishabh Kapoor, Aditya Bachiller, Pilar Jorvekar, Ronit R. Rodriguez-Criado, Daniel Manso, Luis J. Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Guwahati India Department of Computer Science and Information Systems Birla Institute of Technology and Science Goa Pilani India Robotics and Artificial Vision Laboratory University of Extremadura Badajoz Spain Department of Computer Engineering Pune Institute of Computer Technology Pune India Department of Computer Science College of Engineering and Physical Sciences Aston University Birmingham United Kingdom

ISBN: (纸本)9783030625788

Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians’ movements as a pattern to be replicated by robots. It can be argued that one of the main reasons for this to happen is that compiling datasets where real robots are manually controlled, as they would be expected to behave when moving, is a very resource-intensive task. Another aspect that is often missing in datasets is symbolic information that could be relevant, such as human activities, relationships or interactions. Unfortunately, the available datasets targeting robots and supporting symbolic information are restricted to static scenes. This paper argues that simulation can be used to gather social navigation data in an effective and cost-efficient way and presents a toolkit for this purpose. A use case studying the application of graph neural networks to create learned control policies using supervised learning is presented as an example of how it can be used. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Navigation

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Asymptotic Trajectory Tracking of Stratospheric Airships Based on RISE Controllers Under External Uncertainties

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Liu, Can Li, Baoquan Dai, Fengzhi Shi, Wuxi Zhang, Xuebo Tiangong University School of Control Science and Engineering Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin300387 China Tianjin University of Science and Technology College of Electronic Information and Automation Tianjin300222 China Nankai University Institute of Robotics and Automatic Information Systems Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China

For a stratospheric airship under internal and external uncertainties, controller strategies with robust integral sign of the error (RISE) are proposed for asymptotic trajectory tracking control. Specifically, a fully connected neural network (FCNN) is constructed with adaptive weight updating to estimate internal uncertainties of the airship system. Then, a self-tuning RISE controller is designed to track trajectories with compensating external disturbance, which enables gain adjustment in realtime according to system feedback. Based on Lyapunov technique and LaSalle-Yoshizawa corollary extension, system stability is strictly analyzed, and asymptotic convergence performance is obtained for trajectory tracking by the designed controller. Moreover, a RISE controller is designed with fixed gain matrices for the airship based on classic control strategies, and asymptotic tracking is also proved. Finally, numerical simulations are conducted with spiral and hovering control to verify performance of the proposed strategies. © 1965-2011 IEEE.

关键词： Lyapunov methods

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Key Parameters Prediction for Intelligent Control and Energy Optimization Based on MIC-BWO-XGBoost

Key Parameters Prediction for Intelligent Control and Energy...

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Cyber-Energy systems and Intelligent Energy (ICCSIE), International Conference on

作者： Changyao Lv Yaqi Wang Yudong Chen Zhuo Yu Guoliang Hu Hongliang Wu Shuai Li Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai China College of Information Engineering Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes.

关键词： Microwave integrated circuits Accuracy Process control Prediction algorithms Feature extraction Data models Whale optimization algorithms Oxidation Optimization Intelligent control

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Hybrid acoustic-optical underwater communication networks for next-generation cooperative systems: the EUMR experience

Hybrid acoustic-optical underwater communication networks fo...

引用

OCEANS

作者： João Quintas Roberto Petroccia António Pascoal João Cruz Pedro Gois Luca Morlando Marin Stipanov Laboratory of Robotics and Systems in Engineering and Science (LARSyS) ISR/IST University of Lisbon Lisbon Portugal NATO STO Centre for Maritime Research and Experimentation La Spezia Italy

ISBN: (纸本)9781665427883

The past decade has witnessed a flourishing of different physical communication technologies for underwater wireless transmissions systems. Fast paced advances in optical, radio-frequency, or magneto-inductive signals technologies have ushered in a new era of multi-modal communication systems. In a nutshell, the majority of the systems seek to combine the short-range, high-bit rate of the new wave of technologies with the long-range, low-bit rate of the by now de facto acoustic communications solutions. This increasing flexibility opens a new realm of operations and solutions for underwater robotic vehicles working in cooperation. In this paper, we propose a new hybrid acoustic-optical under-water communication network for next-generation cooperative systems. We endeavor to describe its development in the scope of the EU Marine Robots Network project by a team, composed by the NATO STO Centre for Maritime Research and Experi-mentation (CMRE) and the Instituto Superior Tecnico of Lisbon (IST). In particular: the integration of the CMRE Cognitive-Communication Architecture (CCA) with the BlueRay optical modem of IST and its installation in marine robotic vehicles of the Medusa class. laboratory and in-water tests using the Medusa stack and the Medusa class vehicles showcase the potentiality of the proposed network in future cooperative underwater missions.

关键词： Wireless communication Symbiosis Underwater communication Robot kinematics Cooperative systems Modems Acoustics

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航空发动机机匣修复用AlSi10Mg激光金属沉积:显微硬度、磨损和腐蚀行为

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表面工程与再制造 2024年第2期24卷 53-53页

作者： Enjie Dong Tingyu Chang Linjie Zhao Yunhao Xing Jiaxuan Chen Mingjun Chen Junwen Lu Jian Cheng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China Aircraft Repair & Overhaul Plant/Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance Civil Aviation Flight University of China Guanghan 618307 China

基于激光金属沉积(Laser Metal Deposition,LMD)的再制造利用了增材制造的灵活性,为修复或再制造高价值工程零部件提供了一种极具吸引力和性价比的手段。本工作在航空发动机机匣用铸造铝合金板表面熔覆AlSi10Mg合金,当激光功率P=1800 W... 详细信息

基于激光金属沉积(Laser Metal Deposition,LMD)的再制造利用了增材制造的灵活性,为修复或再制造高价值工程零部件提供了一种极具吸引力和性价比的手段。本工作在航空发动机机匣用铸造铝合金板表面熔覆AlSi10Mg合金,当激光功率P=1800 W、送粉速率f=1.6 g/min、扫描速度v=8 mm/s时,获得了孔隙率仅为0.19%的AlSi10Mg修复层。

关键词：铸造铝合金增材制造送粉速率显微硬度激光金属沉积扫描速度激光功率修复层

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Noise-Optimized Signal Processing for TENG-Based Touch Sensing Using I2C Integrated Circuits

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IEEE Sensors Journal 2025年

作者： Moger, Gourav Kakim, Alibek Mubarak, Assem Bushanov, Yersaiyn Kalimuldina, Gulnur Yeshmukhametov, Azamat Nazarbayev University Department of Robotics Engineering Astana Kazakhstan Nazarbayev University School of Engineering and Digital Sciences Department of Mechanical and Aerospace Engineering Astana Kazakhstan LLP MiraiTech Astana Kazakhstan Nazarbayev University Institute of Smart Systems and Artificial Intelligence Advanced Robotics and Mechatronics System laboratory Astana Kazakhstan

Triboelectric nanogenerator (TENG) sensors efficiently convert mechanical stimuli into electrical signals, making them well-suited for touch sensing due to their high sensitivity, durability, and self-powered operation. However, conventional signal acquisition methods introduce noise, affecting measurement accuracy. This paper presents a compact, Inter-Integrated Circuit (I2C)-based signal processing circuit designed to enhance signal fidelity while minimizing noise interference. The system’s performance was evaluated by analyzing sensor response across varying contact areas (50 mm² to 576 mm²) and drop heights, demonstrating a consistently high signal-to-noise ratio (SNR) across impact conditions. A high-frequency impact experiment further confirmed the PCB’s ability to distinguish sensor output from noise. Comparison with direct analog acquisition showed a significant enhancement in SNR, validating the PCB’s effectiveness in noise reduction. The system exhibited a rise time of 3.27 milliseconds, ensuring rapid detection of mechanical stimuli. Additionally, the measured latency of 88.9 ms between impact and signal detection falls within acceptable limits for realtime applications. These results establish the proposed PCB-based signal processing method as a practical solution for improving TENG sensor performance in touch-sensing applications requiring high accuracy and noise resilience. The compact, low-power design further enhances its suitability for integration into wearable electronics, interactive surfaces, and space-constrained systems where conventional bulky processing units are impractical. © 2001-2012 IEEE.

关键词： Network coding

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A Textile-Based Pneumatic Soft Suit for Elbow Joint Rehabilitation

A Textile-Based Pneumatic Soft Suit for Elbow Joint Rehabili...

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

作者： Yan Shen Yu Dang Tianyu Jiang Weiguang Huo Ningbo Yu Jianda Han College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Department of Rehabilitation Medicine The Second Medical Center Chinese PLA General Hospital Beijing China National Clinical Research Center for Geriatric Diseases Beijing China National Key Laboratory of Kidney Diseases Beijing China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Stroke is a disease with a very high mortality rate, and most patients will experience upper limb dysfunction after the disease. Traditional solutions, commonly rigid exoskeletons, have been explored extensively but often fall short due to safety concerns, discomfort, and potential for skin damage owing to their hard attachment mechanisms. To overcome these limitations, this article proposes a textile pneumatic soft suit for elbow joint rehabilitation. This soft suit consists of a modular pneumatic actuator that can help patients with elbow joint flexion and extension rehabilitation training. The design principle is based on the deformation of the textile-based pneumatic bag. The actuator is made of flexible fabric sheets of woven nylon with thermoplastic polyurethane (TPU) coating and 3D printing technology. A mathematical model was developed to describe the relationship between flexion angle and cable length, which could guide the design of the actuator. Experimental validation involved both static and dynamic assessments, confirming the soft suit's capability to meet the requirements of torque and range of the motions. The actuator can provide a starting torque of 7.18 Nm under a pressure of 160 kPa. The suit can provide a range of flexion motion of over 100° for a 1650 g forearm. In the future, we will conduct modeling and further experimental verification of the robot system to complete its control.

关键词： Training Torque Stroke (medical condition) Three-dimensional printing Weaving Skin Safety Elbow Robots Diseases

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Angel's girl for blind painters: An efficient painting navigation system validated by multimodal evaluation approach

arXiv

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arXiv 2021年

作者： Liu, Hang Hu, Menghan Chen, Yuzhen Li, Qingli Zhai, Guangtao Yang, Simon X. Zhang, Xiao-Ping Yang, Xiaokang The Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University The Key Laboratory of Articial Intelligence Ministry of Education The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph The Department of Electrical Computer and Biomedical Engineering Ryerson University

For people who ardently love painting but unfortunately have visual impairments, holding a paintbrush to create a work is a very difficult task. People in this special group are eager to pick up the paintbrush, like Leonardo da Vinci, to create and make full use of their own talents. Therefore, to maximally bridge this gap, we propose a painting navigation system to assist blind people in painting and artistic creation. The proposed system is composed of cognitive system and guidance system. The system adopts drawing board positioning based on QR code, brush navigation based on target detection and bush real-time positioning. Meanwhile, this paper uses human-computer interaction on the basis of voice and a simple but efficient position information coding rule. In addition, we design a criterion to efficiently judge whether the brush reaches the target or not. According to the experimental results, the thermal curves extracted from the faces of testers show that it is relatively well accepted by blindfolded and even blind testers. With the prompt frequency of 1s, the painting navigation system performs best with the completion degree of 89% ± 8.37% and overflow degree of 347% ± 162.14%. Meanwhile, the excellent and good types of brush tip trajectory account for 74%, and the relative movement distance is 4.21 ± 2.51. This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands. In the future, we plan to deploy "Angle's Eyes" on the phone to make it more portable. The demo video of the proposed painting navigation system is available at: https://***/10.6084/***.9760004.v1. © 2021, CC BY.

关键词： Cognitive systems

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