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Methodology for optimizing electrical grounding grids in stratified soils using advanced calculation techniques and evolutionary algorithms

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Swarm and Evolutionary Computation 2025年 95卷

作者： Silva, Carlos Leandro Borges da Pires, Thyago Gumeratto Silva Filho, Antonio Marcelino Bulhões, Junio Santos Belo, Orlando M. Oliveira Rodrigues, Clóves Gonçalves Coimbra, Antonio Paulo Calixto, Wesley Pacheco Electrical Mechanical & Computer Engineering School Federal University of Goias Goiania Goias PC 74.605-220 Brazil Institute of Systems and Robotics Coimbra University CoimbraPC 3030-290 Portugal Department of Informatics School of Engineering University of Minho BragaPC 4710-057 Portugal Electrical Power Systems Study Group Federal Institute of Tocantins Palmas TocantinsPC 77.021-090 Brazil Graduate Program in Production and Systems Engineering Pontifical Catholic University of Goias Goiania Goias PC 74605-010 Brazil Mato Grosso Brazil Technology Research and Development Center Federal Institute of Goias Goiania Goias PC 74.055-110 Brazil

This paper presents a practical methodology for optimizing the geometry of electrical grounding grids at industrial frequencies of 50Hz and 60Hz, integrating advanced calculation techniques and evolutionary algorithms to improve the safety and operational performance of electrical grounding systems. The proposed approach is particularly beneficial for industrial automation and control systems, where effective grounding is necessary to maintain system reliability and prevent downtime. This methodology employs mathematical modeling and computational tools to optimize grid parameters, ensuring compliance with safety standards while reducing operational costs, thus contributing to the overall efficiency of automated systems in industrial environments. The study reports a reduction of up to 66% in the number of vertical rods and 40% in horizontal conductors compared to traditional methods. These results indicate that the proposed methodology can significantly reduce material usage and costs while maintaining electrical safety in accordance with regulatory standards, making it applicable to a wide range of industrial settings, including substations and automated facilities. © 2025 The Authors

关键词： Electric grounding

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Qualitative planning in imperfect information games with active sensing and reactive sensor attacks: Cost of unawareness

arXiv

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arXiv 2021年

作者： Kulkarni, Abhishek N. Han, Shuo Leslie, Nandi O. Kamhoua, Charles A. Fu, Jie The Robotics Engineering Program Dept. of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Electrical and Computer Engineering University of Illinois ChicagoIL60607 United States Raytheon Technologies U.S. Army Research Laboratory

We consider the probabilistic planning problem where the agent (called Player 1, or P1) can jointly plan the control actions and sensor queries in a sensor network and an attacker (called player 2, or P2) can carry out attacks on the sensors. We model such an adversarial interaction using a formal model-a reachability game with partially controllable observation functions. The main contribution of this paper is to assess the cost of P1's unawareness: Suppose P1 misinterprets the sensor failures as probabilistic node failures due to unreliable network communication, and P2 is aware of P1's misinterpretation in addition to her partial observability. Then, from which states can P2 carry out sensor attacks to ensure, with probability one, that P1 will not be able to complete her reachability task even though, due to misinterpretation, P1 believes that she can almost-surely achieve her task. We develop an algorithm to solve the almost-sure winning sensor-attack strategy given P1's observation-based strategy. Our attack analysis could be used for attack detection in wireless communication networks and the design of provably secured attack-aware sensor allocation in decision-theoretic models for cyber-physical systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Formal methods

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Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autononous Driving

arXiv

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arXiv 2023年

作者： Zhang, Xinyu Wang, Li Chen, Jian Fang, Cheng Yang, Lei Song, Ziying Yang, Guangqi Wang, Yichen Zhang, Xiaofei Li, Jun Li, Zhiwei Yang, Qingshan Zhang, Zhenlin Ge, Shuzhi Sam State Key Laboratory of Automotive Safety and Energy the School of Vehicle and Mobility Ts-inghua University Beijing100084 China School of Mechanical and Electrical Engineering China University of Mining and Technology-Beijing Beijing100083 China School of Artificial Intelligence China University of Mining and Technology-Beijing Beijing100083 China College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China Beijing Jingwei Hirain Technologies Co. Inc. Beijing100191 China China Automotive Innovation Cooperation Nanjing211113 China Department of Electrical and Computer Engineering Interactive Digital Media Institute Social Robotics Laboratory National University of Singapore Singapore

Radar has stronger adaptability in adverse scenarios for autonomous driving environmental perception compared to widely adopted cameras and LiDARs. Compared with commonly used 3D radars, latest 4D radars have precise vertical resolution and higher point cloud density, making it a highly promising sensor for autonomous driving in complex environmental perception. However, due to the much higher noise than LiDAR, manufacturers choose different filtering strategies, resulting in a direct ratio between point cloud density and noise level. There is still a lack of comparative analysis on which method is beneficial for deep learning-based perception algorithms in autonomous driving. One of the main reasons is that current datasets only adopt one type of 4D radar, making it difficult to compare different 4D radars in the same scene. Therefore, in this paper, we introduce a novel large-scale multi-modal dataset featuring, for the first time, two types of 4D radars captured simultaneously. This dataset enables further research into effective 4D radar perception algorithms. Our dataset consists of 151 consecutive series, most of which last 20 seconds and contain 10,007 meticulously synchronized and annotated frames. Moreover, our dataset captures a variety of challenging driving scenarios, including many road conditions, weather conditions, nighttime and daytime with different lighting intensities and periods. Our dataset annotates consecutive frames, which can be applied to 3D object detection and tracking, and also supports the study of multi-modal tasks. We experimentally validate our dataset, providing valuable results for studying different types of 4D radars. This dataset is released on https://***/adeptthu/Dual-Radar. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

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An aerodynamic analysis of energy saving car based on computational fluid dynamic using solidworks

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AIP Conference Proceedings 2024年第1期3222卷

作者： R. F. Naryanto A. Setiyawan A. Roziqin S. Maulana F. B. Darsono I. G. M. Andika M. K. Delimayanti R. A. Widodo Mechanical Engineering Department Universitas Negeri Semarang Semarang Indonesia Automotive Engineering Education Universitas Negeri Semarang Semarang Indonesia Computer and Informatics Engineering Department Politeknik Negeri Jakarta Depok Indonesia Master Program in Applied Electrical Engineering Politeknik Negeri Jakarta Depok Indonesia

Improved transportation increased the amount of fuel consumption required. Transportation in Indonesia is the largest oil-consuming sector, with a percentage of 40.1% of the total. Vehicle manufacturers are required to produce a vehicle that has a high level of fuel efficiency. This study aims to determine the aerodynamics of energy-efficient vehicle bodies based on computational fluid dynamics (CFD). This research was conducted using SolidWorks to implement the model. This study examined the variations in airflow velocity at 25, 40, 55, and 70 km/hour. It can be found that the coefficient of drag (Cd) values of the latest body designs with variations in airflow velocity were increased value. The calculation results of the coefficient of drag values were 0.149, 0.154, 0.162, and 0.162, respectively, and the average value was 0.156. In this research, we have found that the energy-saving car body can reduce the drag coefficient compared with the previous study.

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Teaching Autonomous Systems Hands-On: Leveraging Modular Small-Scale Hardware in the robotics Classroom

arXiv

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arXiv 2022年

作者： Betz, Johannes Zheng, Hongrui Zang, Zirui Sauerbeck, Florian Zheng, Y. Rosa Biswas, Joydeep Walas, Krzysztof Dimitrov, Velin Behl, Madhur Krovi, Venkat Mangharam, Rahul The Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA United States The Institute of Automotive Technology Technical University of Munich Germany The College of Engineering and Applied Science Lehigh University BethlehemPA18015 United States The Department of Computer Science University of Texas Austin AustinTX United States The Institute of Robotics and Machine Intelligence Poznan University of Technology Poland The Department of Computer Science University of Virginia CharlottesvilleVA United States College of Engineering Computing and Applied Sciences Clemson University ClemsonSC29634 United States The Toyota Research Institute CambridgeMA02139 United States

Although robotics courses are well established in higher education, the courses often focus on theory and sometimes lack the systematic coverage of the techniques involved in developing, deploying, and applying software to real hardware. Additionally, most hardware platforms for robotics teaching are low-level toys aimed at younger students at middle-school levels. To address this gap, an autonomous vehicle hardware platform, called F1TENTH, is developed for teaching autonomous systems hands-on. This article describes the teaching modules and software stack for teaching at various educational levels with the theme of "racing" and competitions that replace exams. The F1TENTH vehicles offer a modular hardware platform and its related software for teaching the fundamentals of autonomous driving algorithms. From basic reactive methods to advanced planning algorithms, the teaching modules enhance students’ computational thinking through autonomous driving with the F1TENTH vehicle. The F1TENTH car fills the gap between research platforms and low-end toy cars and offers hands-on experience in learning the topics in autonomous systems. Four universities have adopted the teaching modules for their semester-long undergraduate and graduate courses for multiple years. Student feedback is used to analyze the effectiveness of the F1TENTH platform. More than 80% of the students strongly agree that the hardware platform and modules greatly motivate their learning, and more than 70% of the students strongly agree that the hardware enhanced their understanding of the subjects. The survey results show that more than 80% of the students strongly agree that the competitions motivate them for the course. © 2022, CC BY.

关键词： Students

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Automatic petrol and diesel engine sound identification based on machine learning approaches 1

Automatic petrol and diesel engine sound identification base...

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1st International Conference on automotive, Manufacturing, and Mechanical engineering, IC-AMME 2018

作者： Frederick, Halim Winda, Astuti Solihin, Mahmud Iwan Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Engineering Technology and Built Environment UCSI University Cheras Kuala Lumpur56000 Malaysia

Petrol and diesel engine have a significantly different way to convert chemical energy into mechanical energy. In this work, the intelligent system approach is used to automatically identify the type of engine based on the sound of the engine. The combination of signal processing and machine learning technique for automatic petrol and diesel engine sound identification is presented in this work. After a signal preprocessing step of the engine sound, a Fast Fourier Transform (FFT)-based frequency characteristic modelling technique is applied as the feature extraction method. The resulting features extracted from the sound signal, in the form of frequency in the FFT matrix, are used as the inputs for the machine learning, the Support Vector Machine (SVM), step of the proposed approach. The experiment of FFT with SVM-based diesel and petrol engine sound identification has been carried out. The results show that the proposed approach produces a good accuracy in the relatively short training time. Experimental results show the training and testing accuracy of 100 % and 100 % respectively. They confirm the effectiveness of the proposed intelligent automatic diesel and petrol engine sound identification based on Fast Fourier Transform (FFT) and Support Vector Machines (SVMs). © 2019 The Authors, published by EDP Sciences.

关键词： Support vector machines

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engineering a Wide Range Band-Gap of Anatase TiO2 Via Easy-Controlled Solvothermal Method

SSRN

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SSRN 2024年

作者： Mulyanti, Budi Anshar, Aghisna Nuthfah Hasanah, Lilik Wulandari, Chandra Pawinanto, Roer Eka Hamidah, Ida Berhanuddin, Dilla D. Rusydi, Andrivo Study Program of Electrical Engineering Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia TVET Research Center Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Physics Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Industrial Automation and Robotics Engineering Education Universitas Pendidikan Indonesia Jl. Dr..Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Automotive Engineering Education Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Research Complex Universiti Kebangsaan Malaysia Level 4 Selangor Bangi43600 Malaysia Department of Physics National University of Singapore 2 Science Drive 3 Singapore117542 Singapore Singapore Synchrotron Light Source National University of Singapore 5 Research Link Singapore117603 Singapore

Titanium dioxide (TiO2) is a semiconductor material with many applications, such as surface-enhanced Raman spectroscopy (SERS), photocatalysts, water treatment, and photoelectrochemicals. Controlling the properties of anatase TiO2 is typically challenging during TiO2 synthesis. Generally, achieving this control necessitates intricate conditions and processes. The solvothermal method is expected to be easier to control the formation of TiO2 with well-defined morphology and good crystallinity, hence, the band gap can be tuned well. However, there has been a lack of research on the effect of solvents in the solvothermal method of TiO2 synthesis on the optical band gap. Herewith, we report an easy-controlled solvothermal method by varying the type and composition of the solvent to modify the band gap of anatase TiO2. Interestingly, ultraviolet-visible (UV-Vis) analysis reveals an anatase TiO2 optical band gap between 1.66 to 3.60 eV, indicating that TiO2 obtained can be operated in the UV to visible light region. The solvents utilized for the titanium (IV) isopropoxide (TTIP) precursor in TiO2 synthesis are isopropanol (IPA), methanol (META), and ethanol (ETA). X-ray diffraction, Raman spectroscopy, and scanning electron microscopy show anatase TiO2 single crystalline phases synthesized by IPA and ETA solvents and the combination of polycrystalline and amorphous morphology TiO2 synthesized by META solvent. Anatase single crystalline phases are achieved for the solvent mixture with a composition ratio of IPA:ETA solvents of 1:2, 1:1, and 2:1. Our result shows that the optical band gap of single crystalline phase TiO2 can be engineered in a wide range via solvothermal method for green and sustainable material. © 2024, The Authors. All rights reserved.

关键词： Titanium dioxide

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A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and automotive Radars

arXiv

引用

arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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FluxProg 2.0 - Teaching Introductory programming Using Flowcharts with Real and Simulated Robots for The Brazilian robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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Reducing Uncertainty in Pose Estimation under Complex Contacts via Force Forecast

Reducing Uncertainty in Pose Estimation under Complex Contac...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Huitan Mao Jing Xiao Department of Computer Science University of North Carolina Charlotte NC USA Robotics Engineering Program and Department of Computer Science Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

How to reduce uncertainty in object pose estimation under complex contacts is crucial to autonomous robotic manipulation and assembly. In this paper, we introduce an approach through forecasting contact force from simulated complex contacts with calibration based on real force sensing. A constraint-based haptic simulation algorithm is used with sphere-tree representation of contacting objects to compute contact poses and forces, and through matching the computed forces to measured real force data via a regression model, the least-uncertain estimate of the relative contact pose is obtained. Our approach can handle multi-region complex contacts and does not make any assumption about contact types or contact locations. It also does not have restriction on object shapes. We have applied the force forecast approach to reducing uncertainty in estimating object poses in challenging peg-in-hole robotic assembly tasks and demonstrate the effectiveness of the approach by successful completion of contact-rich two-pin and three-pin real peg-in-hole assembly tasks with complex shapes of pins and holes.

关键词： Force Uncertainty Robot sensing systems Task analysis Calibration

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