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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2025年 15274 LNCS卷

作者： Chen, Zhen Granados, Alejandro Li, Xiang Liu, Hongbin Padoy, Nicolas Ren, Hongliang Wu, Jinlin Yuan, Yixuan CAIR HKISI-CAS China King’s College London United Kingdom Harvard University United States University of Strasbourg France Chinese University of Hong Kong China Institute of Automation Chinese Academy of Sciences China

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Non-Singular Terminal Sliding Mode Control Based on Finite-Time Extended State Observer for Robotic systems

Non-Singular Terminal Sliding Mode Control Based on Finite-T...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Gengwei Dai Guanfeng Zhufu Shubo Wang College of Automation Qingdao University Qingdao China

During the control process of robotic system, problems such as slow speed and low accuracy in trajectory tracking control caused by external disturbance and internal parameter uncertainties always happen. Aiming at the above problems, an improved finite-time extend state observer (FTESO) based non-singular fast terminal sliding mode control (NFTSMC) with funnel boundary constraints is proposed in this paper. Firstly, a FTESO with special feedback mechanism, is designed to estimate both the unmeasured states and lumped uncertainties. In addition, by incorporating the error transformation into the sliding mode surface, a novel finite time controller is designed to improve the anti-interference ability and dynamic performance. In order to confirm the superiority of the suggested control strategy, varies comparison simulations are conducted at the end.

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Design of a Highly Reliable Redundant Network Card Supporting the IEEE1588 Protocol 5

Design of a Highly Reliable Redundant Network Card Supportin...

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5th IEEE international conference on Electronics Technology, ICET 2022

作者： Zhang, Bo Yan, Bingjun Liu, Mingzhe Xu, Aidong Wang, Kai Wang, Zhiping 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

ISBN: (纸本)9781665485081

To adapt to the digital and intelligent trend of ship management and meet the requirements of shipborne industrial Ethernet with high reliability and strong real-time performance, this paper develops a shipboard redundant network card with a Zynq7000 series SoC chip as the main controller, and designs the IEEE1588 IP core and PRP IP core on the FPGA side of SoC. the design of the IEEE1588 IPCore can avoid the impact of the jitter of the upper layer protocol stack on the time stamp accuracy;the PRP IPCore implements dual-network redundancy on the FPGA side, reducing the software overhead of the Ethernet protocol stack on the ARM side, and lowers the impact of network switching on synchronization accuracy. through testing, the point-to-point synchronization accuracy of the network card is better than 50 ns, and the dual-network redundancy switch can be quickly completed when the network is disconnected. the design of the network card greatly improves the consistency and accuracy of the internal time of the ship system, and meets the requirements for high reliability, fast fault switching and recovery. © 2022 IEEE.

关键词： System-on-chip

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Artificial Neural Network Models of Multimodal Biometric Authentication System

Artificial Neural Network Models of Multimodal Biometric Aut...

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international conference on Control systems, Mathematical Modelling, automation and Energy Efficiency (SUMMA)

作者： Albina Sabiryanovna Ismagilova Nikita Dmitrievich Lushnikov Department of Information Security Management Institute of Informatics Mathematics and Robotics Ufa University of Science and Technology Ufa Russian Federation

As part of this research, software for multimodal biometric authentication using neural networks is developed to improve the efficiency of information system user authorization. the architectures of artificial neural networks, which are involved in the processes of recognizing a person by facial image and voice, are given. the internationally used databases (DataSet) of images and audio recordings for training of neural networks are considered. the process of training neural networks, the formed database of biometric personal data and the results obtained by the authors are described.

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An Accumulated Error Based Self-Triggered MPC with Adaptive Prediction Horizon for Cyber Physical systems

An Accumulated Error Based Self-Triggered MPC with Adaptive ...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Ning He Wenqian Li Hong Zhou Zhongxian Xu School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Xi'an China Shaanxi Building Materials Technology Group Co. Ltd Xi'an China School of Automation Xi'an University of Post and Telecommunications Xi'an China

An accumulated error based self-triggered model predictive control (AST-MPC) algorithm with an adaptive prediction horizon is proposed for cyber physical systems in this paper. Rather than executing the controller update periodically, the next time of solving the MPC optimization problem is determined according to a new accumulated error based triggering mechanism. Meanwhile, the corresponding prediction horizon is shortened as the state approaches the target regions based on which the communication times and computational complexity of the optimization problem can be reduced simultaneously. Given such a new MPC algorithm, the stability of the considered cyber physical system is analyzed theoretically to guarantee its applicability. Finally, the simulation verification results are provided to illustrate the effectiveness of the algorithm.

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Dynamic SLAM Algorithm Fusing Semantic Information and Geometric Constraints 12

Dynamic SLAM Algorithm Fusing Semantic Information and Geome...

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12th international conference on CYBER Technology in automation, Control, and Intelligent systems, CYBER 2022

作者： Zhou, Dongyi Chang, Yong Hong, Kunlong Song, Yifeng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Shenyang Aerospace University Shenyang China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Traditional visual simultaneous localization and mapping algorithms usually assume that the environment in which the robot is located is static. When dynamic objects appear in the background, the localization accuracy and robustness of the algorithm will be affected by moving targets. Aiming at this problem, an effective VSLAM algorithm that adapts to dynamic scenes is proposed. First, the YOLOv5s object detection algorithm is used to extract the semantic information of the pictures captured by the camera, and the image scene is divided into a static area and a potential dynamic area according to the semantic information. then, the algorithm in this paper only uses the feature points in the static environment when calculating the initial pose, and then combines the epipolar constraints and the weighted dynamic probability to eliminate the dynamic points in the environment. Finally, the initial pose is optimized by calculating all the static points in the environment. Experiments on TUM's RGB dataset show that the proposed algorithm is significantly better than the ORB-SLAM2 system in terms of trajectory accuracy and improves the robustness of SLAM systems in dynamic environments. © 2022 IEEE.

关键词： Object detection

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automation at Sea and Human Factors 15

Automation at Sea and Human Factors

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15th IFAC conference on Control Applications in Marine systems, robotics and Vehicles (CAMS)

作者： Grosser, Linda Wilkinson, Chelsea Oppert, Michelle Banks, Siobhan Clement, Benoit Univ South Australia Behav Brain Body Res Ctr Adelaide SA Australia CROSSING IRL CNRS 2010 Adelaide SA Australia ENSTA Bretagne Brest France

Collisions at sea can have severe effects for humans and the environment, leading to costs for marine organisations. Human factors, particularly fatigue, contribute to more than 80% of maritime collisions. Ships and vessels have become increasingly sophisticated in design and more recently, autonomous navigation systems have been integrated to reduce human errors associated with collisions. the rise in maritime traffic makes these autonomous systems crucial for enhancing safety. A challenge for autonomous navigation systems, causing contention among mariners and within maritime literature, is compliance with COLREG (Convention on the international Regulations for Preventing Collisions at Sea). An emerging solution to this challenge involves the development of a light simulator (COLSim) that leverages historical AIS (Automatic Identification System) data to introduce multiple autonomous vehicles into real-world scenarios, while incorporating the COLREG rules to avoid collision. Acceptance of autonomous navigation systems is important for the future of transportation at sea and is the natural evolution of maritime traffic. As AI is still evolving, humans will continue to play a vital role in the operation of ships and vessels and interpretation of COLREGs. In the future, human-AI interactions will be important for work, health, and organisational safety, where both humans and AI can support each other. Finding a balance between human expertise and AI assistance is essential for the maritime industry's future safety and efficiency. Copyright (c) 2024 the Authors. this is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： COLREGs human factors simulation human-AI interaction machine learning

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A Cube Workpiece Positioning Method Based on Point Structured Light Scanning

A Cube Workpiece Positioning Method Based on Point Structure...

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robotics and Computer Vision (ICRCV), international conference on

作者： Li Cheng Chaohai Xu Shichun Chi Xinyu Mao Sijun Zhu School of Mechanical Engineering Shenyang University Shenyang China Dep. Intelligent Detection and Equipment Shenyang Institute of Automation CAS Shenyang China AVIC XI’AN Aircraft Industry Group Company LTD Xi’an China

In the automation upgrading process of traditional labor-intensive industries, positioning method of workpiece affects the automated operation quality, efficiency, and system cost directly. Traditional workpiece positioning methods based on image vision and line structured light usually require higher professional knowledge or cost, which increase the difficulty for widely application. therefore, this paper proposes a workpiece positioning method based on point structured light scanning for cube-shaped workpieces. Positioning accuracy is analyzed and the feasibility of this method is verified through numerical example. the result of this research provides a precise and low-cost workpiece positioning method for the automation upgrade of traditional labor-intensive industries.

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Assessment of the Utilization of Quadruped Robots in Pharmaceutical Research and Development Laboratories 27

Assessment of the Utilization of Quadruped Robots in Pharmac...

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27th IEEE international conference on Intelligent Engineering systems, INES 2023

作者： Parkinson, Brian Wolf, Adam Galambos, Peter Szell, Karoly Baxalta Innovations GmbH A Takeda Company WienA-1221 Austria Obuda University Doctoral School of Applied Informatics and Applied Mathematics Hungary Obuda University Antal Bejczy Center for Intelligent Robotics Hungary Obuda University Alba Regia Technical Faculty SzekesfehervarH-8000 Hungary

ISBN: (纸本)9798350328516

Drug development is becoming more and more complex and resource-intensive. To reduce the costs and the time-To-market, the pharmaceutical industry employs cutting-edge automation solutions. Supportive robotics technologies, such as stationary and mobile manipulators, exist in various laboratory settings. However, they still lack the mobility and dexterity to navigate and operate in human-centered environments. We evaluate the feasibility of quadruped robots for the specific use case of remote inspection, utilizing the out-of-the-box capabilities of Boston Dynamics' Spot platform. We also provide an outlook on the newest technological advancements and the future applications these are anticipated to enable. © 2023 IEEE.

关键词： Manipulators

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Research on Upper Limb Rehabilitation Action Recognition Method of Unsupervised Contrast Learning Based on Time-domain Multi-scale Feature Fusion 5

Research on Upper Limb Rehabilitation Action Recognition Met...

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5th international conference on Intelligent robotics and Control Engineering, IRCE 2022

作者： Sun, Yuechao Li, Xing Wang, Jianhui Li, Donglin Zhu, Yuxuan School of Information Science and Engineering Northeastern University Shen Yang China School of Electrical Engineering & Intelligentization Dongguan University of Technology Dongguan China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang China

ISBN: (数字)9781665469951

ISBN: (纸本)9781665469951

Vision-based action recognition technology plays a major role in human-robot interaction during the upper limb rehabilitation training of stroke patients with the aid of an upper limb rehabilitation robot. To address the problems that supervised learning requires a large amount of manual labeling, which is time-consuming and inefficient, in this paper, we present an upper limb rehabilitation action recognition method of unsupervised contrast learning based on multi-scale feature fusion and we improves SimCLR by replacing the single-scale CNN with Inception V1 which contains the multi-scale feature fusion module and increasing the temporal dimension based on the idea of the expanded convolutional neural network to fully extract the Spatio-temporal feature information of the actions. the experiment results show that unsupervised contrast learning based on time-domain multi-scale feature fusion achieves recognition accuracy of 92.59% for 8 upper limb rehabilitation actions without extensive manual labeling. It can help patients recover their motor functions through upper limb rehabilitation training. © 2022 IEEE.

关键词： Time domain analysis

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