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Decision Tree Based Decision Optimization Algorithm for Yangqin Performance

Decision Tree Based Decision Optimization Algorithm for Yang...

引用

IEEE international conference on Mechatronics, robotics and automation (ICMRA)

作者： Lin Wei-Lun School of Automation China University of Geosciences Wuhan China

As a traditional folk music, the yangqin has a large gap in the extraction of performance style and features compared with western instruments, and the existing decision making of the yangqin played by a robotic arm has relatively low utilization of the instrument surface. To address this research gap, this paper develops a decision tree based decision optimization algorithm for yangqin performance, which obtains the subsequent assignment results from the previous assignment results, the relative position of the central axis of the instrument surface, and other parameters. this paper illustrates the feasibility of this method from the principle, and designs several sets of controlled experiments to demonstrate that this method can effectively reduce the load of the robotic arm system, increase the utilization range of the instrument surface, and make the allocation results more similar to human habits.

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Selected Development Trends of TECIS 20th

Selected Development Trends of TECIS

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20th IFAC conference on Technology, Culture, and international Stability (TECIS)

作者： Kopacek, Peter Doyle-Kent, Mary TU Wien Inst Mech & Mechatron IHRT Favoritenstr 9-11-E325A4 A-1040 Vienna Austria Waterford Inst Technol Dept Engn Technol Waterford X91 KOEK Ireland

automation, and closely related information systems are, naturally innate, and integrated ingredients of all kinds of objects, systems, and social relations of the present day reality. this is the reason why this contribution treats the phenomena and problems of this automated/information society in a historical manner with a wider, structural framework, giving special emphasis to TECIS. the classical international Federation of Automatic Control's (IFAC) topic of social effects is continually evolving and is moving towards human-machine cooperation. this means that automation technologies require a more interdisciplinary educated workforce. In addition developing countries need access to the newest technology to efficiently and effectively improve their industries. this contribution benchmarks selected important development trends of the Technical committee 9.5 (TECIS). It outlines the social aspects of automation, cost orientated automation, semi-automated assembly and disassembly (end of life), mechatronics systems and robotics, cooperative robotics, engineering ethics and diversity and inclusion in automation. As well as looking forward to future development trends it also looks backwards at the history of automation in the context of TECIS. Copyright (C) 2021 the Authors.

关键词： Social aspects Cost Oriented automation SME-oriented automation Semi-Automated Assembly and Disassembly (EoL) Mechatronic systems and robotics Engineering Ethics Diversity and Inclusion

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Research of Control Methods of a Spherical Parallel Mechanism Using Intelligent Data Processing

Research of Control Methods of a Spherical Parallel Mechanis...

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international conference on Modern Electrical and Energy systems (MEES)

作者： A. Derkachenko O. Polyvoda Yu. Lebedenko K. Kalinina Automation Robotics and Mechatronics Department Kherson National Technical University Kherson Ukraine Information and Computer Technologies Department Kyiv National University of Technologies and Design Kyiv Ukraine

the work is devoted to the research and development of a software and hardware platform based on control methods of a spherical parallel mechanism (SPM) with tracking of changes in the position of a human head with the help of a camera and a computer using intelligent data *** article explores the relevance and advantages of SPMs, emphasizing their high precision, enhanced mobility, reliability, and lightweight design. the paper deals with an important aspect of controlling SPMs, which directly influences their performance. the control methods for SPMs vary based on the specific tasks and operational requirements, such as actuator-based control, sensor-based control, closed-loop control, and adaptive control are *** research additionally investigates the problems of forming tasks for SPMs and the need for improved methods, especially for applications involving human-robot interaction, dangerous works, and camera positioning tasks. To resolve these problems, the study proposed a software-hardware platform that remotely controls SPMs by tracking changes in the position of the human head using a camera and a computer. By employing OpenCV and Dilb libraries for face recognition and control point tracking, the proposed platform enables intuitive and clear control of the *** article presents the mathematical operations involved in calculating the rotation angles of the SPM based on the tracked human head movements. the obtained rotation angles serve as inputs for the servomotors, allowing precise control over the mechanism's *** results of the study demonstrate the effectiveness of the proposed software-hardware platform in controlling the SPM based on human head movements. the platform's ability to accurately track and convert head movements into servo rotation values enables remote and intuitive control of the SPM, making it a promising direction for future research in the field of robotics and automation.

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Aspect-Ratio and Scale Aware Rotated Defect Detection for Fiber-reinforced Composites

Aspect-Ratio and Scale Aware Rotated Defect Detection for Fi...

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Computer Vision, Image and Deep Learning (CVIDL), international conference on

作者： Yuanye Xu Yuanhao Liu Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Institute of Automation University of Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350373820

ISBN: (纸本)9798350373837

Detecting surface defects in carbon fiber-reinforced composites (FRCs) during prepreg stacking is crucial for ensuring product quality. Traditional methods using horizontal bounding boxes (HBBs) for defect detection often lead to overlapping boxes and inaccurate results. this paper proposes an Aspect-Ratio and Scale Aware Detector network (ARSADet) specifically designed for rotated defect detection in FRCs. the network incorporates a Gabor convolutional network for feature extraction, an aspect-ratio and scale-aware label assignment method, and a newly established FRCs Oriented Defect Detection dataset (FODD). Evaluation on the FODD dataset demonstrates superior performance compared to existing methods.

关键词： Deep learning Stacking Detectors Optical fiber networks Feature extraction Product design Quality assessment

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A Container Cloud Elastic Scaling Method Based on GRU Attention Mechanism

A Container Cloud Elastic Scaling Method Based on GRU Attent...

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Computer Engineering and Intelligent Control (ICCEIC) international conference on

作者： Yue Zhang Yong Sun Chunhe Song Pengpei Gao 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

ISBN: (数字)9798331507992

ISBN: (纸本)9798331508005

In modern container cloud computing environments, achieving efficient elastic scaling is crucial to optimizing resource utilization and improving system performance. this paper proposes a new prediction model based on gated recurrent unit (GRU) and attention mechanism for load prediction and elastic scaling strategy optimization. the model uses the time series processing capability of GRU combined with the optimization characteristics of the attention mechanism to improve the accuracy and real-time performance of load prediction. Experimental results show that compared with traditional methods, the model can more accurately capture the load change trend and achieve more agile and efficient resource scheduling and management, thereby effectively reducing resource waste and improving service quality. this study provides a novel and effective solution for elastic scaling in container cloud environments.

关键词： Cloud computing Attention mechanisms Computational modeling System performance Time series analysis Containers Predictive models Resource management Optimization Load modeling

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A Novel Energy Based Ground Movement Detection Technique using Seismic Signal 5

A Novel Energy Based Ground Movement Detection Technique usi...

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5th international conference on Information systems and Computer Networks, ISCON 2021

作者： Chakraborty, Anisom Mallick, Ankit Nemalidinne, Srinivasa Reddy Krishna Vadali, Siva Ram Aruchamy, Srinivasan Nageli, Vinayak Shriniwas Robotics Automation CSIR-CMERI Durgapur India CAIR-DRDO Bengaluru India

ISBN: (纸本)9781665403412

Event detection using seismic signals is a problem of great significance. though several techniques have been developed, achieving an acceptable event detection performance in an outdoor environment is difficult to accomplish. In this paper, a ground movement detection technique is proposed using the energy of acquired seismic signal in different spectral ranges. Performance of the proposed method is tested with an experimental setup including a geo-phone and a data acquisition system. Analysis of results from experimental data indicate that the proposed method renders significant (≈90%) reduction in false alarm probability besides providing ≈ 8% improvement in event detection accuracy, over amplitude and energy thresholding approaches. © 2021 IEEE.

关键词： Data acquisition

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Improving Few-Shot Code Generation with Prompt Selection and Augmentation Techniques in Large Language Models

Improving Few-Shot Code Generation with Prompt Selection and...

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Computers and Artificial Intelligence Technologies (CAIT), international conference on

作者： On Tai Wu Frodo Kin Sun Chan Yan Nei Law Department of Computer Science The University of Hong Kong Hong Kong Hong Kong Industrial Artificial Intelligence & Robotics Centre Hong Kong

ISBN: (数字)9798331530891

ISBN: (纸本)9798331530907

Few-shot prompting and step-by-step reasoning have enhanced the capabilities of Large Language Models (LLMs) in tackling complex tasks including code generation. In this paper, we introduce a prompt selection and augmentation algorithm aimed at improving mathematical reasoning and robot arm operations. Our approach incorporates a multi-stage example augmentation scheme combined with an example selection scheme. this algorithm improves LLM performance by selecting a set of examples that increase diversity, minimize redundancy, and increase relevance to the question. When combined with the Program-of-thought prompting, our algorithm demonstrates an improvement in performance on the GSM8K and SVAMP benchmarks, with increases of 0.3% and 1.1% respectively. Furthermore, in simulated tabletop environments, our algorithm surpasses the Code-as-Policies approach by achieving a 3.4% increase in successful task completions and a decrease of over 70% in the number of examples used. Its ability to discard examples that contribute little to solving the problem reduces the inferencing time of an LLM-powered robotics system. this algorithm also offers important benefits for industrial process automation by streamlining the development and deployment process, reducing manual programming effort, and enhancing code reusability.

关键词： Codes automation Service robots Large language models Redundancy Process control Manuals Programming Cognition Prompt engineering

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Leveraging Latent Temporal Features for Robust Fault Detection and Isolation in Hexacopter UAVs

Leveraging Latent Temporal Features for Robust Fault Detecti...

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international conference on Autonomous Robots and Agents, ICARA

作者： Shivaan Sehgal Aakash Maniar Harikumar Kandath Deepak Gangadharan Robotics Research Center IIIT-Hyderabad Hyderabad India Computer Systems Group IIIT-Hyderabad Hyderabad India

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

this paper introduces a novel approach for fault detection and localization in a motor of a Hexacopter UAV. the proposed two-stage architecture leverages Long Short-Term Memory (LSTM) [1] networks for latent temporal feature extraction and Random Forest [2] for localization. By combining them, we see improved fault detection and isolation performance. Our evaluations show the robustness of this approach in varying noise levels and real-world-like environments. Analysis of computational efficiency in rapid detection shows that the model identified faults within 2–5 time steps of the flight. Finally, we show that the proposed method surpasses classical statistical models and deep learning techniques in terms of overall accuracy (96.78 %).

关键词： Location awareness Fault detection Computational modeling Feature extraction Motors Robustness Long short term memory

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Obstacle Avoidance of Multiple Manipulators Based on 3D Artificial Potential Field Method 11

Obstacle Avoidance of Multiple Manipulators Based on 3D Arti...

引用

11th IEEE Annual international conference on CYBER Technology in automation, Control, and Intelligent systems, CYBER 2021

作者： Xiao, Fei Li, Bing Huang, Hailin Xi, Fengfeng School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Ryerson University Department of Aerospace Engineering TorontoONM5B 2K3 Canada

ISBN: (纸本)9781665425278

this paper proposes a multiple manipulators obstacle avoidance algorithm based on the 3D artificial potential field method. the distance model of the manipulators is established to detect the possible collision of the manipulators. the 3D artificial potential field method is used to deal with the obstacle avoidance problem in the operation of multiple manipulators. Consequently, a smooth collision-free trajectory can be obtained, which is dynamically adjusted according to the parameters of potential field. the experimental results with the UR manipulator illustrate that the developed system is efficient and fast in detecting collisions as well as planning paths. © 2021 IEEE.

关键词： Manipulators

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Stability Analysis of Cyber-Physical systems via Dynamic Feedback Linearization and Linear Matrix Inequalities

Stability Analysis of Cyber-Physical Systems via Dynamic Fee...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Rachid Boutssaid Said Kririm Bensalem Boukili Noureddine Chaibi Laboratory of Materials Signals Systems and Physical Modeling Ibn Zohr University Faculty of Sciences Agadir Agadir Morocco Computer Science Signal Automation and Cognitivism Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Nonlinear control is a challenging aspect in modeling and controlling complex systems, specifically Cyber-Physical systems (CPSs), where the system dynamics are inherently nonlinear. robotics and autonomous vehicle applications mandate the need for stability and robustness guarantees despite such nonlinearities. this paper addresses these challenges by employing dynamic feedback linearization, which extends classical feedback linearization by incorporating dynamic compensators to transform nonlinear systems into linear systems via appropriate state, feedback, and compensator transformations. the linear system can be altered to incorporate classical control techniques in a simpler form to analyze. Moreover, the stability of the transformed system will be analyzed extensively based on Lyapunov quadratic functions and Linear Matrix Inequalities (LMIs) to come up with a robust and systematic toolbox for stability analysis. Additionally, its applicative effectiveness to an autonomous vehicle model will demonstrate its usefulness for addressing practical CPS scenarios. this work develops novel knowledge regarding the behavior of nonlinear systems in the framework of stability, and this is crucial for the design and deployment of CPSs in complex applications.

关键词： Linear systems Cyber-physical systems Stability analysis Robustness Feedback linearization Linear matrix inequalities Nonlinear dynamical systems Safety Vehicle dynamics Autonomous vehicles

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