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第43届中国控制会议

作者： Zhipeng Zhang Yanjun Zhang National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper develops an improved direct model reference adaptive control(MRAC) scheme for continuous-time systems with high relative degrees. The proposed adaptive control scheme does not require any prior knowledge of the highfrequency gain, thereby eliminating the design constraints on the sign of high-frequency gain in traditional MRAC ***, this paper incorporates the estimation of tracking error derivatives into the control signal, and constructs a new MRAC law with a tuning gain. Then, the unknown high-frequency gain and unknown MRAC law parameters in the error equation are decoupled, and parameter update laws without prior knowledge of the high-frequency gain are designed. Unlike existing schemes for addressing the unknown high-frequency gain, this scheme does not rely on any additional design conditions and avoids singularity and persistent control switching issues, while still ensuring closed-loop stability and asymptotic output tracking for continuous-time systems with high relative degrees. Finally, the effectiveness of the proposed scheme is demonstrated through the simulation of the aircraft control system.

关键词： Adaptive control high relative degrees high-frequency gain asymptotic output tracking

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A High-precision Calibration Method for Microsurgical Robots: Combining Iterative Least Squares and PSO-Optimized Support Vector Machine 11

A High-precision Calibration Method for Microsurgical Robots...

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11th International Conference on Mechatronics and Robotics Engineering, ICMRE 2025

作者： Pang, Linjun Li, Haiming Gao, Peiyuan Li, Haotian Zhang, He Zhao, Jie Harbin Institute of Technology State Key Lab of Robotics and Systems Harbin China

ISBN: (纸本)9798331509293

Microsurgical robot calibration is essential for achieving high precision in surgical operations. This paper proposes a high-precision calibration approach combining Iterative Least Squares (ILS) for geometric error correction and Particle Swarm Optimization-optimized Least Squares Support Vector Machine (PSO-LSSVM) for non-geometric error compensation. Experimental results show that the proposed method reduces positioning errors from 3.2541 mm to 0.2310 mm through geometric calibration, achieving a 92.90 % accuracy improvement, and further reduces the error to 0.0749 mm after non-geometric error compensation. These results underscore the effectiveness of the proposed approach in enhancing the precision of robotic systems used in microsurgery, © 2025 IEEE.

关键词： Error compensation

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A Two-Stage Time-Optimal Trajectory Planning Algorithm with No Inverse Kinematics for Manipulator

A Two-Stage Time-Optimal Trajectory Planning Algorithm with ...

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第43届中国控制会议

作者： Wensong Fan Tao Cai Kebing Lu Panpan Yang Haimei Qing National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper studies the time-optimal trajectory planning for manipulator. Conventional time-optimal trajectory planning utilizes the inverse solution, interpolation and intelligent optimization algorithms to search for the shortest time, making the process rather complex. To address this issue, we incorporate the kinematic equations and state transition equations into the existing Two-Stage algorithm used in unmanned aerial vehicles(UAVs), resulting in significantly improved computational speed and accuracy of the robotic arm's operation. The first stage predefines some resulting points related to path points and optimizes the robotic arm's kinematics and motion constraints as soft constraints to provide an initial solution for the second stage. In the second stage, based on the predetermined points of each trajectory segment provided by the first stage, the optimization problem is solved without the need for kinematic inverse solutions, in which the time intervals of each trajectory segment serve as optimization variables and the robotic arm's kinematics and motion constraints are used as hard constraints for optimization. Subsequently, the obtained joint points are interpolated using fifth-degree polynomials to form continuous joint trajectories. Comparative experiments with an improved particle swarm optimization algorithm verify that the proposed method exhibits higher optimization efficiency and achieves shorter optimized times.

关键词： Manipulator Time-Optimal Trajectory Planning Two-Stage Algorithm Kinematics

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A High-precision Calibration Method for Microsurgical Robots: Combining Iterative Least Squares and PSO-Optimized Support Vector Machine

A High-precision Calibration Method for Microsurgical Robots...

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Mechatronics and Robotics Engineering (ICMRE), International Conference on

作者： Linjun Pang Haiming Li Peiyuan Gao Haotian Li He Zhang Jie Zhao State Key Lab of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798331509293

ISBN: (纸本)9798331509309

关键词： Support vector machines Accuracy Medical robotics Error compensation Kinematics Microsurgery Calibration Iterative methods Reliability Particle swarm optimization

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Progress on intelligent metasurfaces for signal relay,transmitter,and processor

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Light(Science & Applications) 2025年第4期14卷 886-901页

作者： Chao Qian Longwei Tian Hongsheng Chen ZJU-UIUC Institute Interdisciplinary Center for Quantum InformationState Key Laboratory of Extreme Photonics and InstrumentationZhejiang UniversityHangzhouChina ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab.of Advanced Micro/Nano Electronic Devices&Smart Systems of ZhejiangZhejiang UniversityHangzhouChina Jinhua Institute of Zhejiang University Zhejiang UniversityJinhuaChina Shanghai Key Laboratory of Navigation and Location-Based Services Shanghai Jiao Tong UniversityShanghaiChina

Pursuing higher data rate with limited spectral resources is a longstanding topic that has triggered the fast growth of modern wireless communication ***,the massive deployment of active nodes to compensate for propagation loss necessitates high hardware expenditure,energy consumption,and maintenance cost,as well as complicated network interference *** metasurfaces,composed of a number of subwavelength passive or active meta-atoms,have recently found to be a new paradigm to actively reshape wireless communication environment in a green way,distinct from conventional works that passively adapt to the *** this review,we offer a unified perspective on how intelligent metasurfaces can facilitate wireless communication in three manners:signal relay,signal transmitter,and signal *** start by the basic modeling of wireless channel and the evolution of metasurfaces from passive,active to intelligent *** with various deep learning algorithms,intelligent metasurfaces adapt to cater for the ever-changing environments without human ***,we overview specific experimental advancements using intelligent *** conclude by identifying key issues in the practical implementations of intelligent metasurfaces,and surveying new directions,such as gain metasurfaces and knowledge migration.

关键词： gain metasurfaces intelligent metasurfaces signal transmitter signal processor active nodes signal relay wireless communication wireless communication techniqueshoweverthe

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Disentangled latent factors for muti-cause treatment effect estimation 6

Disentangled latent factors for muti-cause treatment effect ...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhao, Zhuoyue Wang, Haotian Xu, Liyang Wang, Qian Tang, Yuhua Department of Intelligent Data Science National University of Defense Technology Changsha410073 China Intelligent Game and Decision Lab. Academy of Military Science Beijing100071 China Institute for Quantum Information State Key Laboratory of High-Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

Existing methods estimate treatment effects from observational data and assume that covariates are all confounders. However, observed covariates may not directly represent confounding variables that influence both treatment and outcome. They always include variables that only affect the treatment or the outcome. In addition, for multi-dimensional binary treatments, disentangled methods are mainly designed for binary variables and ignore the impact of multi-cause treatment variables on the inference of latent factors. To address these two issues, based on variable decomposition and proxy inference, we propose the Disentangled Latent Factors for Multi-cause Treatment Estimation (DEMTE) algorithm. It utilizes an identifiable autoencoder to infer and disentangle latent factors based on the joint distribution of variables in observational data. DEMTE evaluates the treatment effect on the disentangled factors. Synthetic experiments and semi-synthetic experiments demonstrate the effectiveness of the inference and disentanglement techniques and our method achieves more accurate treatment effect estimation. © 2024 Institute of Physics Publishing. All rights reserved.

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Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks 38

Rethinking the Membrane Dynamics and Optimization Objectives...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Shen, Hangchi Zheng, Qian Wang, Huamin Pan, Gang College of Artificial Intelligence Southwest University China Chongqing Key Laboratory of Brain Inspired Computing and Intelligent Chips China The State Key Lab of Brain-Machine Intelligence Zhejiang University China College of Computer Science and Technology Zhejiang University China

Despite spiking neural networks (SNNs) have demonstrated notable energy efficiency across various fields, the limited firing patterns of spiking neurons within fixed time steps restrict the expression of information, which impedes further improvement of SNN performance. In addition, current implementations of SNNs typically consider the firing rate or average membrane potential of the last layer as the output, lacking exploration of other possibilities. In this paper, we identify that the limited spike patterns of spiking neurons stem from the initial membrane potential (IMP), which is set to 0. By adjusting the IMP, the spiking neurons can generate additional firing patterns and pattern mappings. Furthermore, we find that in static tasks, the accuracy of SNNs at each time step increases as the membrane potential evolves from zero. This observation inspires us to propose a learnable IMP, which can accelerate the evolution of membrane potential and enables higher performance within a limited number of time steps. Additionally, we introduce the last time step (LTS) approach to accelerate convergence in static tasks, and we propose a label smooth temporal efficient training (TET) loss to mitigate the conflicts between optimization objective and regularization term in the vanilla TET. Our methods improve the accuracy by 4.05% on ImageNet compared to baseline and achieve state-of-the-art performance of 87.80% on CIFAR10-DVS and 87.86% on N-Caltech101. The code is available at https://***/StephenTaylor1998/IMP-SNN. © 2024 Neural information processing systems foundation. All rights reserved.

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Single-Core 7.2-Tb/s (800-Gb/s×9) MDM Self-Homodyne Coherent Transmission over Weakly-Coupled 10-Mode Fibre 49

Single-Core 7.2-Tb/s (800-Gb/s×9) MDM Self-Homodyne Coheren...

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49th European Conference on Optical Communications, ECOC 2023

作者： Qiao, Gang Long, Chengbin Yang, Yu Xu, Zhaopeng Zuo, Mingqing Wang, Shangcheng Liu, Lulu Shen, Lei Luo, Jie Ji, Honglin He, Zhixue Chen, Zhangyuan Hu, Weisheng Li, Juhao Peng Cheng Laboratory Shenzhen China State Key Lab of Advanced Optical Communication Systems and Networks Peking University Beijing00871 China State Key Lab of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Optical Fibre and Cable Manufacture Technology YOFC Wuhan China

ISBN: (纸本)9781839539954

We propose a mode-division-multiplexing (MDM) self-homodyne coherent system over weakly-coupled multiple-ring-core 10-mode fibre and experimentally demonstrate single-core 7.2-Tb/s (5.64-Tb/s net rate) transmission with 800-Gb/s data rate for each of the 9 information-bearing modes using 80-GBaud probabilistic constellation-shaped 64-QAM signals. © The Institution of Engineering & technology 2023.

关键词： Single mode fibers

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Laplacian Welsch Regularization for Robust Semisupervised Learning

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IEEE Transactions on Cybernetics 2022年第1期52卷 164-177页

作者： Ke, Jingchen Gong, Chen Liu, Tongliang Zhao, Lin Yang, Jian Tao, Dacheng PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology Nanjing China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China UBTECH Sydney Artificial Intelligence Centre University of Sydney DarlingtonNSW Australia

Semisupervised learning (SSL) has been widely used in numerous practical applications where the labeled training examples are inadequate while the unlabeled examples are abundant. Due to the scarcity of labeled examples, the performances of the existing SSL methods are often affected by the outliers in the labeled data, leading to the imperfect trained classifier. To enhance the robustness of SSL methods to the outliers, this article proposes a novel SSL algorithm called Laplacian Welsch regularization (LapWR). Specifically, apart from the conventional Laplacian regularizer, we also introduce a bounded, smooth, and nonconvex Welsch loss which can suppress the adverse effect brought by the labeled outliers. To handle the model nonconvexity caused by the Welsch loss, an iterative half-quadratic (HQ) optimization algorithm is adopted in which each subproblem has an ideal closed-form solution. To handle the large datasets, we further propose an accelerated model by utilizing the Nyström method to reduce the computational complexity of LapWR. Theoretically, the generalization bound of LapWR is derived based on analyzing its Rademacher complexity, which suggests that our proposed algorithm is guaranteed to obtain satisfactory performance. By comparing LapWR with the existing representative SSL algorithms on various benchmark and real-world datasets, we experimentally found that LapWR performs robustly to outliers and is able to consistently achieve the top-level results. © 2013 IEEE.

关键词： Large dataset

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Medical image registration and its application in retinal images:a review

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Visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： Computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

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