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IEEE International Conference on systems, Man and Cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods Design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning Cybernetics

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Dynamic Collision Avoidance Using Velocity Obstacle-Based Control Barrier Functions

arXiv

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arXiv 2025年

作者： Huang, Jihao Zeng, Jun Chi, Xuemin Sreenath, Koushil Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Institute of Intelligence Science and Engineering Shenzhen Polytechnic University Shenzhen China Hybrid Robotics Group The Department of Mechanical Engineering UC Berkeley United States

Designing safety-critical controllers for acceleration-controlled unicycle robots is challenging, as control inputs may not appear in the constraints of control Lyapunov functions (CLFs) and control barrier functions (CBFs), leading to invalid controllers. Existing methods often rely on state-feedback-based CLFs and high-order CBFs (HOCBFs), which are computationally expensive to construct and fail to maintain effectiveness in dynamic environments with fast-moving, nearby obstacles. To address these challenges, we propose constructing velocity obstacle-based CBFs (VOCBFs) in the velocity space to enhance dynamic collision avoidance capabilities, instead of relying on distance-based CBFs that require the introduction of HOCBFs. Additionally, by extending VOCBFs using variants of VO, we enable reactive collision avoidance between robots. We formulate a safety-critical controller for acceleration-controlled unicycle robots as a mixed-integer quadratic programming (MIQP), integrating state-feedback-based CLFs for navigation and VOCBFs for collision avoidance. To enhance the efficiency of solving the MIQP, we split the MIQP into multiple sub-optimization problems and employ a decision network to reduce computational costs. Numerical simulations demonstrate that our approach effectively guides the robot to its target while avoiding collisions. Compared to HOCBFs, VOCBFs exhibit significantly improved dynamic obstacle avoidance performance, especially when obstacles are fast-moving and close to the robot. Furthermore, we extend our method to distributed multi-robot systems. Copyright © 2025, The Authors. All rights reserved.

关键词： State feedback

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Inquiring Natural Language Processing Capabilities on Robotic systems through Virtual Assistants:A Systemic Approach

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Journal of Computer Science Research 2023年第2期5卷 28-36页

作者： Ioannis Giachos Evangelos C.Papakitsos Petros Savvidis Nikolaos Laskaris Department of Industrial Design&Production Engineering University of West AtticaEgaleoAthens12241Greece Research Laboratory of Electronic Automation Telematics and Cyber-Physical SystemsUniversity of West AtticaEgaleoAthens12241Greece

This paper attempts to approach the interface of a robot from the perspective of virtual *** assistants can also be characterized as the mind of a robot,since they manage communication and action with the rest of the world they exist ***,virtual assistants can also be described as the brain of a robot and they include a Natural Language Processing(NLP)module for conducting communication in their human-robot *** work is focused on inquiring and enhancing the capabilities of this *** problem is that nothing much is revealed about the nature of the human-robot interface of commercial virtual ***,any new attempt of developing such a capability has to start from ***,to include corresponding capabilities to a developing NLP system of a virtual assistant,a method of systemic semantic modelling is proposed and *** this purpose,the paper briefly reviews the evolution of virtual assistants from the first assistant,in the form of a game,to the latest assistant that has significantly elevated their *** there is a reference to the evolution of their services and their continued offerings,as well as future *** paper presents their structure and the technologies used,according to the data provided by the development companies to the public,while an attempt is made to classify virtual assistants,based on their characteristics and ***,a robotic NLP interface is being developed,based on the communicative power of a proposed systemic conceptual model that may enhance the NLP capabilities of virtual assistants,being tested through a small natural language dictionary in Greek.

关键词： Natural language processing Robotic systems Virtual assistant Human-robot interface

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

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arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

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NBV-HRR: Next Best View Planning Network for Highly Reflective Region Restoration in Robotic 3-D Scanning

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IEEE/ASME Transactions on Mechatronics 2024年

作者： Ouyang, Jun Liu, Daohui Jia, Peng Liu, Xinyu Liu, Xingjian Sun, Yu Dalian University of Technology Institute of Robotics and Intelligent Systems the State Key Laboratory of High-Performance Precision Manufacturing Dalian116024 China University of Toronto Department of Mechanical and Industrial Engineering TorontoONM5S 3G8 Canada

Three-dimensional scanning of highly reflective surfaces is a challenge faced in industrial metrology. The high dynamic range (HDR) technique offers a solution by fusing images taken at various exposures. However, its effectiveness is limited in regions where reflectivity exceeds the camera's dynamic range. To address this issue, this article introduces a next best view (NBV) planning network for the restoration of highly reflective regions, named NBV-HRR. Unlike traditional NBV networks focused on complete shape reconstruction utilizing global features, NBV-HRR targets the restoration of localized regions lost due to reflection, utilizing both global and local features. To accurately evaluate each view, a cross-attention-based module is devised to fuse features of varying dimensions. For network training, a dataset containing 70 400 training samples was collected from over 1000 highly reflective industrial parts in both simulation and real scenes. Experimental results demonstrated that the proposed NBV-HRR network achieved an average restoration rate of 99.3% within three NBV predictions, significantly outperforming the HDR technique (83.7%). © 2024 IEEE.

关键词： Restoration

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Design of a Novel Modular Flux Switching Permanent Magnet Resolver

Design of a Novel Modular Flux Switching Permanent Magnet Re...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Wenyuan Mi Jincheng Yu Zaixin Song Kuang Yang Zheng Cai Hang Zhao School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong SAR China Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

Permanent magnet (PM) resolvers are highly employed with the ascent of the electric machine speed. In this digest, a novel modular flux switching PM (FSPM) resolver is designed based on the FSPM machine. By removing the stator yoke, the flux path in each tooth coil is fixed and the total harmonic distortion (THD) of the output voltage is reduced to only 0.37%. Moreover, the proposed 12/16 FSPM resolver can be adapted to fit different rotor poles under the same mechanical support with different modular units (e.g., 6/8 and 10/8 FSPM resolver). Therefore, it can be applied in electric machines with variable rotor pole pairs.

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Recognition of Dynamic Grasping Motion through Feature Extraction for Teleoperation

Recognition of Dynamic Grasping Motion through Feature Extra...

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WRC Symposium on Advanced robotics and automation (WRC SARA)

作者： Yanping Dai Wenyuan Chen Ning Xi Wenxue Wang State Key Laboratory of Robotics 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 Department of Industrial and Manufacturing Systems Engineering Emerging Technologies Institute University of Hong Kong Hong Kong China

Detecting human movement intentions and transmitting human operational capabilities to robots is of great significance for teleoperations. However, the difference in kinematic structure between human hands and robotic manipulators brings difficulties to teleoperation mapping. In this paper, we present an approach to hand grasp recognition and mapping based on feature extraction to drive heterogeneous remote manipulator. The hand grasp data set HUST recorded with a data glove was used for this study. The data were preprocessed and their features were extracted by PCA. A neural network-based classifier was obtained through offline training of human grasping activities. We compared different network models and selected the network with the best performance based on the training time and the task requirements of teleoperation. The experimental results showed that the recognition accuracy of dynamic grasping motion with feature extraction is higher than that without feature extraction and can be up to 97.47%. Finally, we validated the feasibility of this method to tele-operate an Barrett hand through online experiments. Our proposed method provides an effective approach of mapping natural human grasping operations to heterogeneous robotic teleoperation systems.

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A Quantum-Like Human Learning Optimization Algorithm 8th

A Quantum-Like Human Learning Optimization Algorithm

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Ling Huang, Yi Qian, Chaolin Kang, Xing Zhang, Anfa Pardalos, Panos M. Fei, Minrui Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Sino-European School of Technology Shanghai University Shanghai200444 China Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida GainesvilleFL32611 United States

ISBN: (纸本)9789819602933

Human Learning Optimization (HLO) is a novel potential and promising meta-heuristic, which is developed based on a simplified human learning model. In recent years, the hypothesis that the human cognitive process obeys the laws of quantum rather than classical probability has been successfully used to explain a variety of seemingly "irrational" judgment and human decision-making behaviors, and the independent evidence for this hypothesis has been provided from different experiments. Inspired by this hypothesis, this paper introduces a quantum cognition model of humans into HLO and proposes a quantum-like human learning optimization algorithm (QHLO), in which the belief and its change in human brains during the learning process is simulated and implemented in the search of the algorithm. The developed QHLO is validated on the benchmark functions, and the performance is compared with one recent HLO variants, two quantum-inspired meta-heuristics and two recent binary meta-heuristics. The experimental results show that that the presented QHLO inherits the advantages of HLO and has better global search ability as its diversity is further enhanced with the integration of the quantum cognition model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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Multiparametric atomic force microscopy imaging of single native exosomes

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生物化学与生物物理学报（英文版） 2021年第3期53卷 385-388页

作者： Mi Li Xinning Xu Ning Xi Wenxue Wang Xiaojing Xing Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China Cancer Hospital of China Medical University Shenyang 110042China Liaoning Cancer Hospital&Institute Shenyang 110042China Department of Industrial and Manufacturing Systems Engineering The University of Hong KongHong Kong 999077China

The advent of atomic force microscopy(AFM)provides a novel powerful tool for addressing biological issues in their native *** uses a sharp tip mounted at the end of a micro-fabricated cantilever to probe the specimens immobilized on the *** with other high-resolution imaging and mea-surement techniques(***-resolution optical microscopy,scan-ning electron microscopy,transmission electron microscopy,and magnetic/optical tweezers),the unique merit of AFM is that it is able to simultaneously acquire the structures and properties of living biological samples under aqueous conditions with unprece-dented spatiotemporal resolution(nanometer spatial resolution and millisecond temporal resolution)[1],making AFM an invalu-able platform for revealing the underlying mechanisms guiding life *** wide applications of AFM in molecular and cell biology provide considerable novel insights into the physi-ological/pathological processes[2].Particularly,in recent years,a new AFM imaging mode,which is called peak force tapping(PFT)mode[3],emerges as a promising way for correlating the topography of the specimens with the mechanics of *** PFT mode,the vibrating AFM tip indents the sample at each sam-pling point to record force curves,and the peak force of the force curve is used as the feedback[4].By analyzing the force curves,several types of mechanical properties of the specimens can be real-timely visualized,and thus PFT mode is also called multiparametric imaging AFM[5],offering novel possibilities for resolving the fine structures and properties of fragile biological specimens.

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