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9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020

作者： Dudi, Tanishk Singhal, Rahul Kumar, Rajesh Al-Sumaiti, Ameena Do, Ton Duc MNIT Dept. of Mechanical Engg. Jaipur India Khalifa University of Science and Technology Dept. of Electrical and Computer Engg. United Arab Emirates Nazarbayev University Dept. of Robotics and Mechatronics Kazakhstan

ISBN: (纸本)9781728156729

Flight safety and fuel consumption are major concerns of airline industry. En route civil aircraft may encounter hindrances such as bad weather patches, prohibited areas, and flight constraints. Robust path planning ensures maximum safety of the aircraft, crew members and passengers in unknown environment such as uncertain wind direction and drag from low pressure areas. This paper presents the robust path generation methodology near to the line of sight from starting aerodrome to the target aerodrome. This methodology confined the search space on the aerospace map to the nearby hindrance from the line of sight and then plan a robust path for the aircraft with the help of voronoi diagram. The voronoi diagram for the airspace map gives cells on the grid map, where each cell is equidistant from the hindrances. For these cells, the shortest robust path is evaluated using Dijkstra algorithm. The simulations for the shortest robust path on the airspace map were carried out for the proposed methodology and voronoi diagram for the full airspace map. The results obtained show that unnecessary clearances from the hindrances are avoided, and the computational time to evaluate the shortest robust path has been considerably reduced. © 2020 IEEE.

关键词： Motion planning

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Emergence of human oculomotor behavior from optimal control of a cable-driven biomimetic robotic eye

arXiv

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arXiv 2022年

作者： Alitappeh, Reza Javanmard John, Akhil Dias, Bernardo van Opstal, A. John Bernardino, Alexandre Institute for Systems and Robotics Instituto Superior Técnico ISR Lisbon Portugal Dept. Biophysics Donders Centre for Neuroscience Radboud University Nijmegen Netherlands University of Science and Technology of Mazandaran Behshahr Iran

In human-robot interactions, eye movements play an important role in non-verbal communication. However, controlling the motions of a robotic eye that display similar performance as the human oculomotor system is still a major challenge. In this paper, we study how to control a realistic model of the human eye with a cable-driven actuation system that mimics the six degrees of freedom of the extra-ocular muscles. The biomimetic design introduces novel challenges to address, most notably the need to control the pretension on each individual muscle to prevent the loss of tension during motion, that would lead to cable slack and lack of control. We built a robotic prototype and developed a nonlinear simulator, for which we compared different approximation techniques to control its gaze behavior. In the first approach, we linearized the nonlinear model, using a local derivative technique, and designed linear-quadratic optimal controllers to optimize a cost function that accounts for accuracy, energy expenditure, and movement duration. The second method uses a recurrent neural network that learns the nonlinear system dynamics from sample trajectories of the system, and a non-linear trajectory optimization solver that minimizes a similar cost function. For both approaches we developed a method to determine the required cable pretension at movement onset. We focused on the generation of rapid saccadic eye movements with fully unconstrained kinematics, and the generation of control signals for the six cables that simultaneously satisfied several dynamic optimization criteria. The model faithfully mimics the three-dimensional rotational kinematics and dynamics observed for human saccades. Interestingly, just like for the primate eye, the six cables organized themselves into the appropriate antagonistic muscle pairs that minimize the amount of muscle co-contraction. Our experimental results indicate that while both methods yielded similar results, the nonlinear method is more

关键词： Kinematics

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Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition

Efficient Robust Principal Component Analysis via Block Kryl...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Shun Fang Zhengqin Xu Shiqian Wu Shoulie Xie School of Information Science and Engineering Wuhan University of Science and Technology China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial Systems Signal Processing RF & Optical Dept. Institute for Infocomm Research A*STAR Singapore

Robust principal component analysis (RPCA) is widely studied in computer vision. Recently an adaptive rank estimate based RPCA has achieved top performance in low-level vision tasks without the prior rank, but both the rank estimate and RPCA optimization algorithm involve singular value decomposition, which requires extremely huge computational resource for large-scale matrices. To address these issues, an efficient RPCA (eRPCA) algorithm is proposed based on block Krylov iteration and CUR decomposition in this paper. Specifically, the Krylov iteration method is employed to approximate the eigenvalue decomposition in the rank estimation, which requires $O(ndrq+n(rq)^{2})$ for an $(n\times d)$ input matrix, in which $q$ is a parameter with a small value, $r$ is the target rank. Based on the estimated rank, CUR decomposition is adopted to replace SVD in updating low-rank matrix component, whose complexity reduces from $O(rnd)$ to $O(r^{2}n)$ per iteration. Experimental results verify the efficiency and effectiveness of the proposed eRPCA over the state-of-the-art methods in various low-level vision applications.

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Wireless Sensor Networks and Green Networking for 6G communication- An Overview

Wireless Sensor Networks and Green Networking for 6G communi...

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Computational Intelligence, Communication technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Dibyahash Bordoloi Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Turkey Faculty of Engineering Research Center for AI and IoT University of Kyrenia Kyrenia Turkey Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun RS CSE Graphic Era University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of technology and Management (GLBITM) Greater Noida India

Wireless sensor networks and green networking have been major research areas in the field of communication technology for the past few decades. In particular, the development of 6G communication systems has brought renewed focus on these areas, as the demands for higher data rates, more diverse applications, and lower energy consumption continue to increase. The use of wireless sensor networks in 6G communication systems has been widely explored in the literature, and has shown great potential for a wide range of applications, including environmental monitoring, industrial process control, and healthcare. However, a key challenge in the deployment of these networks is ensuring their energy efficiency, as the demands on the network will be much higher than in previous generations. To address this challenge, researchers have proposed various green networking techniques, such as energy harvesting and low-power communication protocols, which have been shown to significantly reduce the energy consumption of the sensors. In addition to improving the energy efficiency of wireless sensor networks, researchers have also studied their reliability, scalability, and adaptability. These properties are important in 6G communication systems, as the demands on the network are expected to be much higher than in previous generations. Researchers have proposed various methods to improve the reliability, scalability, and adaptability of wireless sensor networks, including the use of error-correction codes, redundant communication channels, and machine learning algorithms.

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Broad-Bandwidth Photonic Quantum Memory

Broad-Bandwidth Photonic Quantum Memory

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Quantum 2.0, QUANTUM 2022

作者： Arnold, Nathan T. Victora, Michelle Goggin, Michael E. Kwiat, Paul G. Dept. of Physics University of Illinois Urbana-Champaign 1110 West Green Street UrbanaIL61801 United States RightHand Robotics Inc 237 Washington Street SomervilleMA02143 United States Truman State University 100 E Normal Street KirksvilleMO63501 United States Illinois Quantum Information Science and Technology Center UIUC UrbanaIL61801 United States

Photonic quantum memories will play an essential role in synchronizing nodes of quantum networks. Here we present a system that can store polarization and time-bin qubits for up to 12.5 µs over a THz bandwidth. &... 详细信息

ISBN: (纸本)9781957171111

关键词： Bandwidth

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Social engineering attack types and prevention techniques- A survey

Social engineering attack types and prevention techniques- A...

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Computational Intelligence, Communication technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Shruti Bhatla Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Turkey Department of Computer Science and Engineering Graphic Era Hill University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) Greater Noida India

The term "Cyber Security" is getting more and more popular and important over the last few years. Since computers and most of the devices are connected to the internet, they are likely to be hacked by the hackers. In the past, this issue was not a big problem, because not every device is required to be connected to the internet or the internet was not popular as today. But the case has changed over the years. All the changes in the technology area also changed the cyber-attack models as well. With the development of technology and the change of usage of the internet over the last years cyber-attacks have become more common and popular by the hackers. Hackers have discovered that they have an opportunity to steal or earn money in a short time without having to spend too much effort. These days, the type of cyber-attacks is not the same as the ones in the past. As time passes, the cyber-attack methods are also changing and evolving. Today, hackers are using more advanced and effective cyber-attack methods compared to past years. There are many methods that are impossible to cover all of them in this article. Our main focus will be on social engineering attacks in this article. Social engineering attacks use different approaches to cyber attacking. Unlike trying to explode a victim’s social media password etc. using advanced exporting programs, algorithms or techniques, social engineering attacks focus on fooling victims into providing their data to hackers by themselves without using or implementing any password cracking, exploiting techniques etc. We will go over what social media engineering is, type of social engineering methods, what countermeasures can be used to protect from social engineering and more in this article.

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“Should I Lead?” Feasibility Study of User Perception on Following-Robot for Gait Assessment

“Should I Lead?” Feasibility Study of User Perception on F...

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International Conference on Advanced robotics (ICAR)

作者： Alessandra Sorrentino Bruno Ferreira Paulo Menezes Jorge Batista Jorge Dias Laura Fiorini Pietro Benvenuti Filippo Cavallo Department of Industrial Engineering University of Florence Florence Italy Dept. of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal Khalifa University of Science and Technology Khalifa University Center for Autonomous Robotic Systems Abu Dhabi UAE BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy

Current techniques of gait assessment rely on wearable sensors, pressure-sensitive walkway systems, and optical motion capture systems. A less invasive and more portable solution could be represented by a mobile robot that follows the user during the gait activity. The main idea behind this work relies on finding the best robot configuration for less invasive gait analysis with high acceptability from the end users. To this aim, two follow-me configurations have been designed: human-leader (i.e. the robot follows the person from behind), and robot-leader (i.e. robot follows the person from the front). We asked 27 young participants to test both modalities and to evaluate their perception of the robot in 5 domains: comfort, expected conformity, safety, trust, and unobtrusiveness. Additionally, we extracted quantitative parameters related to the walking experience from the data recorded by the platform and we analyzed them in tandem with the qualitative results. The results reported that robot-leader configuration tended to be more appreciated in terms of comfort, trust, and safety. On the contrary, the human-leader configuration is perceived as less obtrusive, less invasive, and in line with users' expectations. Considering the gait assessment application, we expect the human-leader configuration to return more promising and accurate results.

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Solution for Agri Disaster Using Climate Changes Adaptation by Ml

Solution for Agri Disaster Using Climate Changes Adaptation ...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： L. Ganesh R. Prasanna Venkatesh Kaushal Kumar Khushboo Kumari Sangeeta Borkakoty A. Raju Robotics and Automation Dept. Rajalakshmi Engineering College Chennai Tamilnadu India Department of Mechanical Engineering SACS MAVMM Engineering College Madurai Tamilnadu India Department of Botany School of Life Sciences Mahatma Gandhi Central University Bihar India Department of Computer Science & Electronic University of Science & Technology Meghalaya Department of Commerce KLEF Vaddeswaram Green Field Vijayawada

This paper proposes using good sized getting to know fashions to recognize lesions of cotton leaves in the context of pictures of the reaping within the subject. Cotton is among the maximum economically essential plant harvests, as it's far grown all over the international. Its spread in tropical areas has made it the goal of a wide variety of farming irritations and illnesses, necessitating succesful plans. moreover, the consequences of commonplace disturbances and disorders are difficult to isolate inside the early stages, and the author may additionally battle to locate the suitable visible verification of a scientific difficulty. To help in resolving the difficulty, it contemporary inquiry proposes a solution that takes into consideration substantial training within the filtering of cotton leaves, making it possible to reveal the cotton yield's health and make higher judgments approximately its management. The studying models GoogleNet like Resnet50, which use convolutional cerebrum associations, performed an accuracy of 86.6 percentage and 89.2 percentage, respectively. assist vector machines, Closest k-pals, faux creativeness associations, and neuro-tender are some of the extraordinary as well as everyday tactics again for treatment of photographs. The convolutional cerebellum networks ended up being 25% extra unique, implying that this method can upload to a more strong and short investigation of the flora looking to fill inside the field.

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Semiconductor Manufacturing Industry: Assessment, Challenges, and Future Trends

Semiconductor Manufacturing Industry: Assessment, Challenges...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Yasmin Musa Khalid Tantawi Maged Mikhail Jeffrey Ma Dalal Alharthi Larry Flatt Lyn Potter Department of Career Readiness Motlow State Community College Smyrna TN Department of Engineering Management and Technology University of Tennessee at Chattanooga TN Department of Engineering Technology Purdue University Northwest Hammond IN Department of Mechanical Engineering Saint Louis University Saint Louis MO College of Applied Science and Technology University of Arizona Tuscan AZ Director of the Robotics and Automation Center Motlow State Community College McMinnville TN Dept. of Engineering Systems Tech. Chattanooga State Community College Chattanooga State Community College Chattanooga TN

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

In this work we evaluate the state of the semiconductor manufacturing industry and its challenges and trends. Future trends in the industry are analyzed from three perspectives: the evolution of Industry 4.0, the advances in semiconductor materials, and the impact of the Covid-19 Pandemic. The semiconductor manufacturing industry witnessed an acute decline in the United States and other regions in the two decades prior to the CoVid-19 pandemic. The decline was only uncovered after the chip shortage of 2021 that resulted from the severe supply chain disruption. Trends in the industry were analyzed from three perspectives: Industry 4.0, advances in materials, and the Post-pandemic era. As a result of the evolution of the fourth generation of industry (Industry 4.0), trends in semiconductor manufacturing include robotization, which caused the industry to become the largest market for industrial robotics since 2020, and an all-time peak globalization. The semiconductor industry is a very globalized industry with corporates from different parts of the world taking part in the production of the final product. Although some materials such as carbon and Gallium Nitride show promising trends to replace silicon as the material of choice. It will likely not be before two or three decades when a semiconductor material will be able to replace silicon. Challenges for the industry include the shortage of the trained-workforce, and the added inter-country restrictions that may hinder the globalization of the industry.

关键词： Industries COVID-19 Pandemics Service robots Supply chains Globalization Semiconductor device manufacture Market research Silicon Fourth Industrial Revolution

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Prototyping and Conceptualizing Electric Model Vehicles to Enhance Automotive STEM Education: Towards Sustainable E-Mobility

Prototyping and Conceptualizing Electric Model Vehicles to E...

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Education Conference (GeCon), IEEE German

作者： Mbadiwe S. Benyeogor Abubakar. A. Dahiru Andrew O. Benyeogor Oladayo O. Olakanmi Akintayo Akintola Baki Adeiza Sodiq Institute of Physics University of Münster Münster Germany Abuja - FCT National Information Technology Development Agency (NITDA) Nigeria CTE - Computer Science & Robotics Lab. International Leadership of Texas Aggieland Texas USA Dept. of Electrical & Electronic Engineering University of Ibadan Ibadan Nigeria Ralph Alabi Engineering Centre Nigeria Society of Engineers (NSE) Lagos Nigeria Dept. of Vocational & Technical Education University of Benin Benin City Nigeria

Considering the rapid technological advances in the automotive industry and the trend toward electric vehicles, there is an apparent need to modify and simplify the design and prototyping of electric model vehicle systems, in order to enhance their usability in schools for demonstrating and teaching automotive engineering and other related science, technology, engineering, and mathematics (STEM) concepts. Therefore, this paper proposes an easy-to-prototype template of an educational model vehicle to teach automotive-related STEM subjects, covering automechanics, autotronics, and coding. The model vehicle is portable and affordable, making it a useful tool for teaching basic principles, design, and construction of automotive systems in schools. The functions of various components in the model vehicle are described using appropriate schematics, and the impact of the device on classroom pedagogy was assessed over three years. The study found that the method can be used in schools to teach automotive technology and highlight the benefits of recycling waste materials. Therefore, we anticipate that our work will pique the curiosity of students and stimulate their imagination in preparation for the industry as it transitions toward e-mobility and eco-friendly manufacturing.

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