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arXiv 2025年

作者： Li, Wanyi Wei, Wei Luo, Yongkang Wang, Peng State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences 999077 Hong Kong

Few-shot class-incremental learning (FSCIL) poses significant challenges for artificial neural networks due to the need to efficiently learn from limited data while retaining knowledge of previously learned tasks. Inspired by the brain’s mechanisms for categorization and analogical learning, we propose a novel approach called Brain-inspired Analogical Mixture Prototypes (BAMP). BAMP has three components: mixed prototypical feature learning, statistical analogy, and soft voting. Starting from a pre-trained Vision Transformer (ViT), mixed prototypical feature learning represents each class using a mixture of prototypes and fine-tunes these representations during the base session. The statistical analogy calibrates the mean and covariance matrix of prototypes for new classes according to similarity to the base classes, and computes classification score with Mahalanobis distance. Soft voting combines both merits of statistical analogy and an off-shelf FSCIL method. Our experiments on benchmark datasets demonstrate that BAMP outperforms state-of-the-art on both traditional big start FSCIL setting and challenging small start FSCIL setting. The study suggests that brain-inspired analogical mixture prototypes can alleviate catastrophic forgetting and over-fitting problems in FSCIL. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

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Collaborative turning and jumping control of a cyborg locust via sensory stimulation

Collaborative turning and jumping control of a cyborg locust...

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International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

作者： Peng Liu Songsong Ma Shen Liu Yao Li Bing Li School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9781665449670

In this study, we describe the first-ever demonstration of the turning and jumping control of locusts based on electrical stimulation, which can realize a cyborg jumper. In terms of perception, walking distance, speed, payload, maneuverability, and adaptability to complex environments, cyborgs can reveal unmatchable advantages to insect-scale artificial robots. Herein, live locusts (Locusta migratoria) were selected as the study platform. Antennae and cercus stimulations using electrical pulses were applied to elicit the insect to turn and jump. We examined both the turning angle and the angular velocity by tuning the stimulus amplitude or frequency. It is found the turning rate induced by antenna stimulation can be graded. Besides, the stimulation of the cercus at the distal abdomen triggered the jump reliably. Moreover, the directional jumping control of the locust was achieved by the collaboration of turning and jumping control. Such results provide the potential to establish a more precise and more efficient model to develop a direction-controllable cyborg jumper.

关键词： Legged locomotion Wireless communication Protocols Insects Collaboration Electrical stimulation Turning

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Research on Intrusion Detection of Industrial Control System Based on FastICA-SVM Method 7th

Research on Intrusion Detection of Industrial Control System...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Chen, Haonan Liu, Xianda Wang, Tianyu Zhang, Xuejing College of Information Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Beijing China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Beijing China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030786083

As an important part of guard system, intrusion detection systems have great significance to the security of industrial control systems. Cause the industrial control systems of the on-site environment is often very complicated, the process data extracted on-site have a wide variety of features, and they always have complex associations and are not independent. The intrusion detection algorithms for traditional industrial control systems often do not solve this problem, which results in a decrease in the accuracy, precision and high false negative rate (FNR), false positives rate (FPR). Aiming at solving the current problems, this paper proposes an algorithm combining the Fast Independent Principal Component Analysis (FastICA) and Support Vector Machine (SVM). Finally compared with the SVM and PCA-SVM algorithms, the experimental results show that the accuracy rate has been significantly improved and slight FPR. © 2021, Springer Nature Switzerland AG.

关键词： Intrusion detection

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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IEEE International Conference on Industrial Technology (ICIT)

作者： Sichao Zhang Wei Liang Yinlong Zhang Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Department of Automation Technology ABB Corporate Research Sweden Vasteras Sweden

ISBN: (纸本)9781728119496

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method.

关键词： Wireless communication Conferences Semantics Hidden Markov models Interference Markov processes Radiofrequency interference

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Distributed Non-Fragile State Estimation for discrete nonlinear systems with parameter uncertainties

Distributed Non-Fragile State Estimation for discrete nonlin...

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第40届中国控制会议

作者： Ping Xu Huaiyu Wu Xiujuan Zheng Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

The distributed non-fragile state estimation problem is proposed for a class of discrete nonlinear systems with parameter uncertainties. Considering the parameter uncertainty of the system and the stochastic disturbance of the corresponding filter gain, a distributed non-fragile recursive state estimator is designed. Based on the strategy of linear consensus, a distributed non-fragile recursive filter is derived for each sensor node. Due to some uncertain parameters of the system, the upper bound of the filter error covariance is further derived. Then, the filter gain is obtained by minimizing the upper bound of the error covariance. Finally, an indoor localization system for mobile robots is provided to verify the proposed state estimator.

关键词： Non-fragile state estimation distributed filtering parameter uncertainties wireless sensor network

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Multi-Domain Image Super-Resolution Generative Adversarial Network for Low-Resolution Person Re-Identification

Multi-Domain Image Super-Resolution Generative Adversarial N...

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第40届中国控制会议

作者： Siwen Chen Huaiyu Wu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

Person re-identification（ReID） is an important task in video surveillance *** address the issue that various low-resolutions and scale mismatching always exist in the real world,a multi-domain image-to-image translation network,termed Multi-Domain image Super-Resolution Generative Adversarial Network（MSRGAN）,is proposed to learn the mapping relationship between the various low-resolution domains and the high-resolution *** can ensure that the transferred image has a similar resolution as in the target *** is also able to keep the identity information of images from low-resolution domain during the *** addition,a novel ReID model,termed CSA-ReID in which channel attention and spatial attention module are introduced,is designed to learn resolution-invariant deep *** proposed method achieves 90.7% rank-1 accuracy and 96.4% rank-5 accuracy on multiple low-resolutions Market-1501 *** experimental results prove that the proposed method achieves promising generalization ability and accuracy compared with the state-of-theart methods.

关键词： person re-identification cross-resolution super-resolution attention

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Magnetic-Actuated Flexible Instruments with Enhanced Bending Capability through Magnetic Distribution Optimization

Magnetic-Actuated Flexible Instruments with Enhanced Bending...

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IEEE International Conference on automation Science and Engineering (CASE)

作者： Yuanrui Huang Runyu Ma Jian Hu Mingcong Chen Jian Chen Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of General Engineering Beihang University Beijing China Centre of AI and Robotics (CAIR) Hong Kong Institute of Science & Innovation Chinese Academy of Sciences

Magnetically-actuated flexible surgical robot has promising applications for ultra-narrow and tortuous orifices. However, maximizing its bending capability and manipulability remains a significant hurdle for clinical use. In this study, we introduce an objective function that can accurately predict a catheter's bending angle with given numbers of internal permanent magnets (IPMs) under various magnetic fields through iterative calculation. The optimal magnets distribution that yields the maximal controllable bending angle, could be determined by optimizing this objective function. The effectiveness of this method is validated through simulations and experiments. Additionally, we propose a simple control scheme to control the bending angle of the magnetically-actuated catheter based on the piecewise constant curvature model. The experimental results demonstrate that the proposed method significantly improves the motion accuracy of the catheter. The catheter with the optimized magnet distribution achieved superior tracking performance with an Integral Absolute Error (IAE) of 1.08 rad·s and maximal controllable bending angle of 150°.

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Multi-UAV Cooperative 3D Coverage Path Planning Based on Asynchronous Ant Colony Optimization

Multi-UAV Cooperative 3D Coverage Path Planning Based on Asy...

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第40届中国控制会议

作者： Hui Li Yang Chen Zhihuan Chen Huaiyu Wu Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

UAVs carrying visual sensors to capture the defects on the building surface has the advantages of high efficiency,low cost,flexibility and *** kind of inspection task is called coverage path planning problem in 3 D *** the target to be detected is a large complex building,multi-UAV collaboration is usually ***,how to obtain the optimal path of multi-UAV becomes a great *** order to solve the problem,Asynchronous Ant Colony Optimization（AACO）,which makes multiple ant colonies move forward asynchronously,is proposed here to conquer the ***,the random sampling method is used to get the potential UAV waypoints in the 3 D free environment,based on which a Primitive Coverage Graph（PCG） is ***,the visibility matrix and coverage rate are defined to quantify the coverage performance of UAV path ***,Asynchronous Ant Colony Optimization combined with reward strategy is proposed to solve the problem by selecting jump cities in ***,several simulations are provided to verify the feasibility and effectiveness of the algorithm.

关键词： 3D Coverage Path Planning Asynchronous Ant Colony Optimization Path Primitive

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Mobile Robot Automatic Aiming Method Based on Binocular Vision

Mobile Robot Automatic Aiming Method Based on Binocular Visi...

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第40届中国控制会议

作者： Honglian Xiang Lei Cheng Huaiyu Wu Yang Chen Yingnan Gao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

Aiming at the task that robots can automatically aim and accurately shoot projectiles to hit enemy armor plates in the complex confrontation environment,an automatic aiming control method is ***,the two-dimensional position coordinates of the target are obtained by the improved object detection ***,the depth information of the target is obtained by the binocular depth ***,the actual three-dimensional position information of the target is obtained by combining the object detection and depth ***,by calculating the attitude angle of the pan-tilt,the angle that can guide the pan-tilt to aim and rotate is obtained,thus realizing automatic aiming control on the mobile *** many real confrontation experiments,high precision and real-time performance are obtained,which proves the rationality and feasibility of this method.

关键词： Automatic aiming Accurate hitting Object detection Binocular ranging

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Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

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IEEE International Conference on robotics and Biomimetics

作者： Wenze Shang Ruisen Huang Wei-Hsin Liao Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

sEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their $sEMG$ signals were utilized to evaluate muscle fatigue. The results indicate that $sEMG$ from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue.

关键词： Legged locomotion Limbs Frequency-domain analysis Biomimetics Human-robot interaction Muscles Fatigue Feature extraction Time-domain analysis Robots

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