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2022 IEEE MIT Undergraduate Research Technology Conference, URTC 2022

作者： Golemi, Kleo Akhter, Arsalan Bhada, Shamsnaz V. Worcester Polytechnic Instituite Electrical and Computer Engineering Worcester United States Worcester Polytechnic Instituite Robotics Engineering Worcester United States

ISBN: (纸本)9781665473453

Most engineering projects require a team of various disciplines to work together. Although with different disciples there can be issues in communication between disciplines due to jargon and a lack of understanding each role's capabilities. [1] This is especially true during the early stages of the project. Systems engineers have used SysML as a model-based systems engineering tool to compose and articulate tasks as well as display the collaboration of each discipline towards a goal unifying communication and setting a clearly defined purpose. This paper shows how SysML and UML is used in organizing and articulating the tasks of an interdisciplinary research team, consisting of: robotics, communication, and system engineers toward the goal of fire detection. © 2022 IEEE.

关键词： interdisciplinary model-based systems engineering (MBSE) SysML systems engineering

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FAIR-FATE: Fair Federated Learning with Momentum 23rd

FAIR-FATE: Fair Federated Learning with Momentum

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23rd International Conference on Computational Science, ICCS 2023

作者： Salazar, Teresa Fernandes, Miguel Araújo, Helder Abreu, Pedro Henriques Centre for Informatics and Systems Department of Informatics Engineering of the University of Coimbra University of Coimbra Coimbra Portugal Institute of Systems and Robotics Department of Electrical and Computer Engineering of the University of Coimbra University of Coimbra Coimbra Portugal

ISBN: (纸本)9783031359941

While fairness-aware machine learning algorithms have been receiving increasing attention, the focus has been on centralized machine learning, leaving decentralized methods underexplored. Federated Learning is a decentralized form of machine learning where clients train local models with a server aggregating them to obtain a shared global model. Data heterogeneity amongst clients is a common characteristic of Federated Learning, which may induce or exacerbate discrimination of unprivileged groups defined by sensitive attributes such as race or gender. In this work we propose FAIR-FATE: a novel FAIR FederATEd Learning algorithm that aims to achieve group fairness while maintaining high utility via a fairness-aware aggregation method that computes the global model by taking into account the fairness of the clients. To achieve that, the global model update is computed by estimating a fair model update using a Momentum term that helps to overcome the oscillations of non-fair gradients. To the best of our knowledge, this is the first approach in machine learning that aims to achieve fairness using a fair Momentum estimate. Experimental results on real-world datasets demonstrate that FAIR-FATE outperforms state-of-the-art fair Federated Learning algorithms under different levels of data heterogeneity. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Momentum

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Underwater Exploration with Sonar of the Flooded Basement of a WW-II Submarine Bunker in the Context of the Digitization of Cultural Heritage

Underwater Exploration with Sonar of the Flooded Basement of...

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OCEANS

作者： Tim Hansen Frederike Buda Andreas Birk Robotics Computer Science and Electrical Engineering Constructor University Bremen

Underwater mapping based on the registration of data from a mechanical scanning sonar (MSS) is presented. The specific use-case is the exploration of the flooded basement of the U-Boot Bunker Valentin in the context of the digitization of this World-War-II memorial. The visibility in the basement, which is inaccessible for divers due to safety reasons, is very poor. Hence, maps are very helpful if not essential for the exploration of this environment, for which - despite its rather recent history - open questions exist. The mapping is conducted with a very robust method in form of Fourier-SOFT 2D (FS2D), which is well suited for real-time registration of the very noisy scans generated with simple motion-compensation from the MSS data. More precisely, the exploration of the bunker basement is conducted with low-cost hardware in form of a BlueROV2 vehicle, simple navigation sensors, and a Ping360 MSS. We show that reasonable maps can be generated in real-time with this equipment when using FS2D.

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Dating Wall Constructions from Brick Sizes in the Flooded Basement of a WW-II Submarine Bunker for the Digitization of Cultural Heritage

Dating Wall Constructions from Brick Sizes in the Flooded Ba...

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OCEANS

作者： Andreas Birk Frederike Buda Tim Hansen Computer Science and Electrical Engineering Constructor University Bremen Robotics

Results from the exploration of the flooded basement of the U-Boot Bunker Valentin are presented. The work is done in the context of the digitization of the bunker, which was constructed during World-War II using substantial amounts of forced labor and which is now a memorial. The presented research deals with walls in the basement for which it is of interest when they were constructed. Using a simple but efficient structured light system, the sizes of the bricks were measured. In combination with the changes in German standards for bricks after WW-II, this gives important clues about the time of construction of the investigated walls.

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Haptic System for Handwriting Training and Classification

Haptic System for Handwriting Training and Classification

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： João P. Ferreira António P. Coimbra Manuel Crisóstomo Department of Electrical Engineering Superior Institute of Engineering of Coimbra Portugal Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Nowadays, handwriting still plays an important role in our lives, even though we live in a progressively more digital era. Therefore, losing the ability to write, whether because of physical or psychological complications, can become a huge handicap. The system described herein aims, in a first stage, to enable handwriting training through haptic guidance. The implementation was performed in Visual Studio and with the use of OpenHaptics toolkit. The second stage consists in character classification, written using a haptic joystick. The pre-eminent procedure for digit classification consists in the use of Histogram of Oriented Gradients coupled with a multiclass Support Vector Machine (HOG-SVM) whereas for letters the strategy involves using a Convolutional Neural Network (CNN).

关键词： Training Support vector machines Visualization Accuracy Shape Writing Time measurement Haptic interfaces Trajectory Convolutional neural networks

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Output Tracking Control of a Nonlinear System Based on Takagi-Sugeno Fuzzy Model: Generalized Partial Eigenstructure Assignment Approach

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IEEE Access 2024年 12卷 18520-18535页

作者： Soltanian, Farzad Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2M9 Canada Shiraz University of Technology Electrical Engineering Faculty Shiraz71557-13876 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2-performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2-performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems. © 2013 IEEE.

关键词： Transient analysis

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AgileVision Academy: Indoor Drone Navigation and Obstacle Avoidance 14

AgileVision Academy: Indoor Drone Navigation and Obstacle Av...

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14th International Conference on Information Technology in Medicine and Education, ITME 2024

作者： Jiang, Haolong Gu, Lingdan Wang, Jiayu Lan, Xiao Liu, Qinyao Wang, Fanxin Xi'an Jiaotong Liverpool University University of Liverpool School of Advanced Technology Department of Electrical and Electronic Engineering Suzhou China Xi'an Jiaotong Liverpool University School of Robotics Department of Intelligence Robotics Engineering With Contemporary Entrepreneurialism Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Information and Computer Science Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Electrical and Electronic Engineering Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Mechatronics and Robotics Suzhou China

ISBN: (纸本)9798350356670

Navigating cluttered indoor environments presents a significant challenge for aerial robots, requiring agility, speed, and a high level of reliability to avoid collisions. This project aims to address this challenge by developing advanced algorithms for lightweight drones, enabling them to reach target location and carrying out delivery efficiently and safely. Utilizing camera data to map and avoid obstacles, we create a system that not only maps and perceives the environment but also navigates its path to the destination. Included in the educational content, this project demonstrates the effectiveness of the technology through practical applications and real-world testing, helping the next generation of engineers accumulate technical experience and broaden their understanding of drone navigation algorithms and applications in system integration. It has a milestone impact on education and development of the drone field. © 2024 IEEE.

关键词： Drones

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Sliding-Mode-Based Control Strategy for a Solar Multi-Port Three-Level DC-DC Converter under Harsh System Uncertainty

Sliding-Mode-Based Control Strategy for a Solar Multi-Port T...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Ganjavi, Amir Gorji, Saman A. Ghoreishy, Hoda Sera, Dezso Queensland University of Technology Centre for Clean Energy Technologies & Practices School of Electrical-Engineering & Robotics Brisbane Australia Deakin University Centre for Smart Power & Energy School of Engineering Melbourne Australia Babol Noshirvani University of Technology Faculty of Electrical and Computer Engineering Babol Iran

ISBN: (纸本)9798350331790

In this paper, a robust control approach using a sliding-mode-based (SLMB) control strategy has been designed for a solar multi-port three-level dc-dc converter that is specifically tailored for harsh environmental conditions, such as solar panel failure and load fluctuations. The multi-port three-level dc-dc converter has one solar input, one buck battery port, and a boost output. The sliding-mode control is designed to regulate the main boost output voltage at the desired magnitude in a three-level control structure, while the maximum power tracking is simultaneously executed for the solar input. To maintain robustness against harsh system uncertainties, a sliding mode control law in which the load and input power parameters are eliminated is constructed. Therefore, the proposed control strategy is theoretically insensitive to input current and load fluctuations. The proposed control strategy's efficacy is validated in simulations, and its performance is compared to that of a well-tuned conventional PI controller. © 2023 IEEE.

关键词： Sliding mode control

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RoboRover - A Jetson Nano Powered Robot Car for Object Following, Obstacle Avoidance, and Wall Following 14

RoboRover - A Jetson Nano Powered Robot Car for Object Follo...

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14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Huynh, Trinh Walter, James Aveta, Federica University of Michigan Robotics Department Ann ArborMI48109 United States Wentworth Insitute of Technology Electrical and Computer Engineering Program BostonMA02115 United States

ISBN: (纸本)9798350304138

An intelligent and self-sufficient robot is essential across a wide range of fields, including transportation, industry, space exploration, and defense. Mobile robots possess the capability to undertake diverse tasks such as handling materials, aiding in disaster scenarios, conducting patrols, and executing rescue operations. As a result, the development of an autonomous robot that can navigate through both unchanging and ever-changing surroundings has become important. The primary objective of mobile robot navigation revolves around ensuring the seamless and secure traversal of the robot through complex environments, starting from an initial position, and reaching a designated goal position. This paper presents the design and implementation of a Jetson Nano powered robot car which uses local sensors to interact with an unknown environment. Object following, obstacle avoidance, and wall following features are built for the car to navigate to reach its desired destinations. © 2023 IEEE.

关键词： Mobile robots

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A study of multifactor quantitative analysis of sports game trends 24

A study of multifactor quantitative analysis of sports game ...

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2024 International Conference on Smart City and Information System, ICSCIS 2024

作者： Wang, Yuefan Gu, Zhongquan Liu, Yuhao Wu, Lihao School of Electrical Engineering Guangzhou City University of Technology Guangzhou Guangdong510800 China School of Mechanical Robotics Engineering Guangzhou City University of Technology Guangzhou Guangdong510800 China School of Computer Engineering Guangzhou City University of Technology Guangzhou Guangdong510800 China

ISBN: (纸本)9798400710155

This study analyzes the effect of momentum on the outcome of tennis matches, using the 2023 Wimbledon men's singles final as an example. The match data was preprocessed, including invalid sample treatment, outlier treatment, data normalization, feature screening and the innovative combination of wavelet analysis and Bayesian Optimization are used in data preprocessing. An ARIMA model was constructed to analyze the effect of match duration on the outcome. The study found that the longer the duration of the match, the more difficult it is to predict. A Pearson correlation analysis model was used to determine the correlation between the distance moved by players and wins and losses. The random forest model analysis showed that serve order, match point, and set point were the key factors influencing the match outcome. Additionally, Djokovic's momentum changes were evaluated through hierarchical analysis, and the model's accuracy was verified using the 2022 Qatar World Cup Final as an example. The study proposes a coaching strategy based on risky decision-making to help coaches effectively coach athletes during matches. © 2024 ACM.

关键词： Risk assessment

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