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arXiv 2023年

作者： Li, Shilei Shi, Dawei Lou, Yunjiang Zou, Wulin Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Xeno Dynamics Control Department Xeno Dynamics Co. Ltd Shenzhen518055 China

Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, The noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ones. To handle this issue, we propose a generalized multi-kernel maximum correntropy Kalman filter for disturbance estimation, which is less conservative by adopting different kernel bandwidths for different channels and exhibits excellent performance both with and without external disturbance. The convergence of the fixed point iteration and the complexity of the proposed algorithm are given. Simulations on a robotic manipulator reveal that the proposed algorithm is very efficient in disturbance estimation with moderate algorithm complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

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Configurability Selection of Robotic Arm with Constrained Task and Environment in Laparoscopic Hysterectomy for Uterus Manipulation

Configurability Selection of Robotic Arm with Constrained Ta...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Chen, Wei Wu, Jiahao Zhou, Jianshu Wang, Hesheng Wang, Yudong Cheung, Tak Hong Liu, Yun-Hui Chinese University of Hong Kong T Stone Robotics Institute Department of Mechanical and Automation Engineering Hong Kong Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China China International Peace Maternity and Child Health Hospital Shanghai Jiaotong University School of Medicine Department of Obstetrics and Gynecology Shanghai China Prince of Wales Hospital Chinese University of Hong Kong Department of Obstetrics and Gynaecology Hong Kong

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Multi-link serial robots have gained growing popularity in robot-Assisted surgeries with the advantages of flexibility and versatility. This type of robot has be introduced into the uterus manipulation in laparoscopic hysterectomy (UMLH) to mitigate the disadvantages of our previous robotic uterus manipulator. Compared with the other surgical tasks (e.g. laparoscope manipulation, orthopedic and neurosurgery surgeries), the UMLH has a more narrow workspace and a stringent task requirement. Selecting the proper initial configuration of the robot is a key issue for such kind of surgical operations. In this paper, we develop a scheme to select appropriate initial configurations for the UMLH. Moreover, our method can satisfy both the static RCM and dynamic RCM. In an dynamic RCM, the task path or trajectory depends on the robot initial pose and arbitrary (or indefinite) with respect to the robot base frame. We also proposed a criterion, i.e. configuration-Type task capability (CTTC), to measure the task capability of a given configuration-Type for the dynamic RCMs. Simulations are carried out to validate our scheme. © 2022 IEEE.

关键词： Neurosurgery

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Improving the Adversarial Robustness of Quantized Neural Networks Via Exploiting the Feature Diversity

SSRN

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SSRN 2022年

作者： Chu, Tianshu Fang, Kun Yang, Jie Huang, Xiaolin Department of Automation Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Department of Automation The Institute of Medical Robotics The MOE Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

Quantized neural networks (QNNs) have become one of the most prevailing approaches in deep learning model compression due to their computation and storage efficiency. However, there is a lack of researches specialized in the adversarial robustness of QNNs, which is important to applications in the security-critical domains. The existing defenses focus on the conventional full-precision networks. It would result in behavioral disparities and degrade the expected performance to be transferred to the QNNs directly. A novel defensive strategy prompts the feature diversity via an orthogonal constraint, which could cooperate well with the quantization. Inspired by this intuition, an orthogonal regularization with quantization is proposed to improve the adversarial robustness of QNNs in this paper. Moreover, it is observed that the quantization is an implicit regularization and is able to alleviate the orthogonal degeneration. The proposed orthogonal regularization with quantization is validated on several typical network architectures and benchmark datasets. The results demonstrate that the proposed method could improve the adversarial robustness against both the white-box and black-box attacks notably. © 2022, The Authors. All rights reserved.

关键词： Network architecture

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When Shannon Meets Nonstochastic Information: Communication and Estimation

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IEEE Transactions on Automatic control 2025年

作者： Zhang, Wentao Zuo, Zhiqiang Zhao, Rui Wang, Yijing Hu, Guoqiang Zhang, Hui Wang, Yaonan Hunan University School of Robotics Changsha410082 China Nanyang Technological University Continental-NTU Corporate Lab Singapore639798 Singapore Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Nanyang Technological University School of Electrical and Electronic Engineering Singapore639798 Singapore National Engineering Research Center for Robot Visual Perception and Control Changsha410082 China Hunan University College of Electrical and Information Engineering Changsha410082 China

This notes focuses on the issue of whether or not the state of a plant can be estimated when the inputs of communication channel involve noise and disturbance simultaneously. It turns out to calculate the maximum capacity of stationary memoryless multiple quasi-access channel under nonstochastic information theory. It is shown that the maximum information rate over such a channel is determined by a convex hull spanned by the zero-error capacities which are specified on the underlying sample spaces. Moreover, the state of a plant could be estimated provided that the maximal information rate is strictly greater than the topology entropy. © 1963-2012 IEEE.

关键词： Communication channels (information theory)

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Tooth segmentation of dental mesh based on improved region growing

Tooth segmentation of dental mesh based on improved region g...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Gu, Chenlan Zhao, Ning Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Orthodontics Shanghai200240 China Shanghai Jiao Tong University Institute of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665436786

Computer-aided design (CAD) systems have gained more and more concern in orthodontics over the last decades. Aimed at tooth segmentation task of three dimension (3D) dental models in orthodontic CAD systems, we propose an efficient and robust framework based on geometric features. To make region growing algorithm flexible and apply it to 3D tooth segmentation, we extend the region similarity description from single-parameter to multi-parameter. A parameter adaptive method is designed to get rid of manual parameter adjustment and raise efficiency. Moreover, we provide a multi-level label optimization algorithm for segmentation refinement. Some experiments are conducted with various dental models from real cases to validate various algorithmic components. The results demonstrate that our pipeline is superior on efficiency and robustness. © 2021 IEEE.

关键词： Efficiency

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An Efficient Planning and control Framework for Quadrotors Based on Heuristic Search and Data-Driven Model Predictive control

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IEEE Transactions on Industrial Electronics 2025年

作者： Wang, Sifei Wang, Yaonan Miao, Zhiqiang Wang, Xiangke He, Wei Wang, Hesheng Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha410082 China National University of Defense Technology College of Intelligence Science and Technology Changsha410073 China Beijing Information Science and Technology University School of Automation Institute of Artificial Intelligence Beijing100083 China University of Science and Technology School of Intelligence Science and Technology Beijing100083 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

This article presents a framework for quadrotors that integrate planning and control, which employs a heuristic depth-first search (HDFS) with data-driven model predictive control (MPC). The proposed framework intends to enable multiquadrotor systems to traverse cluttered environments containing obstacles and disturbances. The heuristic function enables quadrotors to identify a secure route in a timely manner. The heuristic function setup employed by HDFS results in a reduction in the number of rasters accessed, particularly in scenarios that are not labyrinthine. This consequently leads to an enhancement in computational speed for multiquadrotor systems when compared to the A* algorithm. Furthermore, data-driven MPC enhances the nominal model of the quadrotor by modeling the disturbance while tracking the desired states. Consequently, data-driven MPC is capable of attaining superior tracking precision in a disturbance environment when compared to MPC without data-driven. The transformation from the path to the desired states of the quadrotor is achieved through the utilization of B-splines and differential flatness. Simulations and experiments substantiate the efficacy of the proposed approach. © 1982-2012 IEEE.

关键词： Predictive control systems

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A Novel Hybrid Method for Fault Diagnosis of Industrial Equipment Based on Vibration Signals

A Novel Hybrid Method for Fault Diagnosis of Industrial Equi...

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Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Sen Tao Kai Wang Peng Zeng Tianda Yu Hao Wu 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 Shenyang China Nuclear Power Institute of China Chengdu China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China

Industrial equipment reliability is a critical issue that smart manufacturing systems must address. Implementation of online fault diagnosis for industrial equipment is a promising technology that can improve equipment reliability. Vibration analysis is a popular technique for equipment condition monitoring. For the non-linear and non-stationary features of industrial vibration signals, a hybrid model based on wavelet transform (WT), support vector machine (SVM), and grey wolf optimization algorithm (GWO) is proposed. The time-frequency domain features of fault signals are extracted by wavelet transform to solve the non-linearity of signals, and the obtained feature vectors are input into SVM for classification. Aiming at the problem of setting penalty coefficient and kernel function parameters, GWO is introduced to seek hyperparameters by using the hunting principle of wolves. In the experimental part, firstly, the comparison of the GWO-WT-SVM, GWO-SVM and SVM models was carried out. Secondly, Comparison with classical classification algorithms is made. Apparently, the GWO-WT-SVM model achieves higher accuracy than other models in bearing fault diagnosis.

关键词：

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Incorporating Steering Constraints in AGV Path Planning Through Graph Augmentation

Incorporating Steering Constraints in AGV Path Planning Thro...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Liming Zhang Zhimin Han Bo Wang Zhiyun Lin Xiangdong Xu School of Automation Hangzhou Dianzi University Hangzhou P. R. China Zhejiang CoTEK Robotics Co. Ltd Hangzhou P. R. China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen P. R. China Peng Cheng Laboratory Shenzhen P. R. China Wenzhou Institute of Industry & Science Wenzhou P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

In this paper, we introduce an innovative method for the orientation-specific path planning of an Automated Guided Vehicle (AGV) with steering constraints, such as unmanned forklifts. Traditional shortest-path algorithms, which solely consider distance or travel time, are unsuitable for tasks where the AGV’s orientation is crucial. To address this, we have created an augmented graph that inherently incorporates the AGV’s steering constraints and orientation. By utilizing this enhanced graph structure, conventional shortest-path algorithms can be employed to ascertain a path that takes the AGV’s orientation into account. This novel method facilitates more adaptable and secure path planning, while preserving the immediacy required for real-time path planning execution.

关键词： Remotely guided vehicles Path planning Real-time systems Task analysis Standards Robots

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Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving

arXiv

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arXiv 2024年

作者： Hu, Xuemin Chen, Pan Wen, Yijun Tang, Bo Chen, Long School of Artificial Intelligence Hubei University Wuhan430062 China Key Laboratory of Intelligent Sensing System and Security Hubei University Ministry of Education Hubei Wuhan430062 China Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States State Key Laboratory of Multimodal Artificial Intelligence Systems State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an710049 China

Reinforcement learning (RL) has been widely used in decision-making and control tasks, but the risk is very high for the agent in the training process due to the requirements of interaction with the environment, which seriously limits its industrial applications such as autonomous driving systems. Safe RL methods are developed to handle this issue by constraining the expected safety violation costs as a training objective, but the occurring probability of an unsafe state is still high, which is unacceptable in autonomous driving tasks. Moreover, these methods are difficult to achieve a balance between the cost and return expectations, which leads to learning performance degradation for the algorithms. In this paper, we propose a novel algorithm based on the long and short-term constraints (LSTC) for safe RL. The short-term constraint aims to enhance the shortterm state safety that the vehicle explores, while the long-term constraint enhances the overall safety of the vehicle throughout the decision-making process, both of which are jointly used to enhance the vehicle safety in the training process. In addition, we develop a safe RL method with dual-constraint optimization based on the Lagrange multiplier to optimize the training process for end-to-end autonomous driving. Comprehensive experiments were conducted on the MetaDrive simulator. Experimental results demonstrate that the proposed method achieves higher safety in continuous state and action tasks, and exhibits higher exploration performance in long-distance decision-making tasks compared with state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Lagrange multipliers

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A method of laser focusing control in microlaser-induced breakdown spectroscopy

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Plasma Science and Technology 2019年第3期21卷 31-39页

作者： Wei WANG Lanxiang SUN Peng ZHANG Liming ZHENG Lifeng QI Wei DONG Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences

This paper presents a method for the automatic adjustment of the laser defocusing amount in micro-laser-induced breakdown spectroscopy. A microscopic optical imaging system consisting of a CCD camera and a 20× objective lens was adopted to realize the method. The real-time auto-focusing of the system was achieved by detecting the effective pixels of the light spot generated by the laser pointer. The focusing accuracy of the method could achieve 3 μm. The element concentrations of Mn and Ni in low-alloy steels were analyzed at a crater diameter of about 35 μm using the presented method. After using the presented method, the determination coefficients of Mn and Ni both exceeded 0.997, with the root-mean-square errors being 0.0133 and 0.0395, respectively. Scanning analysis was performed on the inclined plane and the curved surface by means of focusing control and non-focusing control. Ten characteristic spectral lines of Fe were selected as the analysis lines. With the focusing control, the average relative standard deviations obtained on the inclined plane and curved surface were both less than 5%, and much less than the values without focusing control, 14.6% and 40.39%.

关键词： LIBS microanalysis ablation crater focusing control

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