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An Open-source Hardware/Software Architecture and Supporting Simulation Environment to Perform Human FPV Flight Demonstrations for Unmanned Aerial Vehicle Autonomy

arXiv

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arXiv 2024年

作者： Xiao, Haosong Krisshnakumar, Prajit Pothuri, Jagadeswara P.K.V. Soni, Puru Butcher, Eric Chowdhury, Souma Mechanical and Aerospace Engineering University at Buffalo BuffaloNY United States Mechanical and Aerospace Engineering University at Buffalo BuffaloNY United States Computer Science and Engineering. University at Buffalo BuffaloNY United States Mechanical and Aerospace Engineering Center for Embodied Autonomy and Robotics University at Buffalo United States

Small multi-rotor unmanned aerial vehicles (UAVs), mainly quadcopters, are nowadays ubiquitous in research on aerial autonomy, including serving as scaled-down models for much larger aircraft such as vertical-take-off-and-lift vehicles for urban air mobility. Among the various research use cases, first-person-view (FPV) RC flight experiments allow for collecting data on how human pilots fly such aircraft, which could then be used to compare, contrast, validate, or train (via imitative learning) autonomous flight agents. While this could be uniquely beneficial, especially for studying UAV operation in contextually complex and safety-critical environments such as in human-UAV shared spaces, the lack of inexpensive and open-source hardware/software platforms that offer this capability along with low-level (complete access) to the underlying control software and data remains limited. To address this gap and significantly reduce barriers to human-guided autonomy research with UAVs, this paper presents an open-source software architecture implemented with an inexpensive in-house built quadcopter platform based on the F450 Quadcopter Frame. This setup uses two cameras to provide a dual-view FPV and an open-source flight controller, Pixhawk. The underlying software architecture, developed using the Python-based Kivy library, allows logging telemetry, GPS, control inputs, and camera frame data in a synchronized manner on the ground station computer. Since costs (time) and weather constraints typically limit numbers of physical outdoor flight experiments, this paper also presents a unique AirSim/Unreal Engine based simulation environment and graphical user interface (GUI) – aka digital twin – that provides a Hardware In The Loop (HITL) setup via the Pixhawk flight controller. We demonstrate the usability and reliability of the overall framework through a set of diverse physical FPV flight experiments and corresponding flight tests in the digital twin. Copyright © 2024, The Au

关键词： Graphical user interfaces

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Towards Automatic Characterization of Nano-Energetic Material Response to Directed Energy 13

Towards Automatic Characterization of Nano-Energetic Materia...

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Energy Harvesting and Storage: Materials, Devices, and applications XIII 2023

作者： Gaines, Timothy Boyle, Camden Hurt, J. Alex Maschmann, Matthew R. Keller, James M. Scott, Grant J. Price, Stanton R. Electrical Engineering and Computer Science Department University of Missouri-Columbia ColumbiaMO65211 United States Mechanical and Aerospace Engineering Department University of Missouri-Columbia ColumbiaMO65211 United States U.S. Army Engineer Research and Development Center VicksburgMS39180 United States

ISBN: (数字)9781510661417

ISBN: (纸本)9781510661400

Nanoenergetic materials offer high-density energy storage that may be reacted to produce heat and release gaseous products. However, the fundamental reaction mechanisms of isolated nanoenergetic fuel particles (typically aluminum - AL) remain poorly understood. In this study, the structure-property relationships of photothermally heated AL nanoparticles are explored using an optical microscope setup and laser-based photothermal heating. Our research explores optical imaging and computer vision techniques to measure distinctive features from images captured before and after directed energy excitation of nanoenergetic particles. These features are used to describe the reactions in the pursuit of creating an automated nanoenergetic material reaction characterization model. Specifically, optical imagery of nano-aluminum particle clusters is taken before and after the reaction is initiated via laser irradiation. Through image preprocessing and registration, we remove untargeted nanoparticle clusters and align the images. We then classify particle reactions into three classes, Spallation, Sintering, or a Combination of both, through an examination of various features derived from our preprocessed imagery. These techniques serve as tools to aid researchers in quantitatively measuring reaction properties, such as loss of mass, and accelerating the search for optimized reaction parameters. © 2023 SPIE.

关键词： Sintering

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Hydrogen and biomethane pathways to achieve sustainable transportation in circular economic concept: A review

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International Journal of Hydrogen Energy 2025年 143卷 403-419页

作者： Saravanakumar, Ayyadurai Sudha, M.R. Chen, Wei-Hsin Pradeshwaran, Vijayakumar Centre for Research in Environment Sustainability Advocacy and Climate Change Directorate of Research and Virtual Education SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India Department of Computer Applications College of Science and Humanities SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Department of Chemistry SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India

Amidst the imperative need to reduce emissions and the rising demand for transportation, the logistics sector is at a crossroads. On a global scale, where road freight plays a significant role in the economy, the search for environmentally friendly fuel alternatives has led to the emergence of biomethane as a potential solution to assist fleets in decarbonizing their operations in the present day. The reliance of the transportation industry on fossil fuels is a cause for concern due to its environmental consequences and the depletion of resources. This study investigates the feasibility of hydrogen and biomethane as an eco-friendly transportation fuel in a circular economy. The analysis focuses on the production method, environmental advantages, and the role of biomethane in closing resource loops. The study examines constraints such as infrastructural development, feedstock availability, and economic viability. The significant findings on hydrogen suggest its strong potential as a sustainable fuel for long-haul heavy vehicles, showing better climate performance even when fossil electricity is used in production. Furthermore, in a circular economy, hydrogen-powered heavy-duty vehicles could become more advantageous than diesel, particularly as diesel faces reduced acceptance due to environmental issues. © 2025 Hydrogen Energy Publications LLC

关键词： Circular economy

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Robust laser self-mixing displacement demodulation via continuous wavelet–Hilbert transform for high-precision accelerometer calibration

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Applied Optics 2025年第16期64卷 4559-4567页

作者： Chang, Zhikun Song, Song Xue, Dongbai He, Chunling Shi, Zhoumiao Yu, Jing Kong, Ming Xie, Yuying Deng, Xiao Li, Tongbao Cheng, Xinbin Institute of Precision Optical Engineering Tongji University Shanghai200092 China Tongji University Shanghai200092 China MOE Key Laboratory of Advanced Micro-Structured Materials Tongji University Shanghai200092 China Shanghai Frontiers Science Center of Digital Optics Tongji University Shanghai200092 China Shanghai Professional Technical Service Platform for Full-Spectrum and High-Performance Optical Thin Film Devices and Applications Tongji University Shanghai200092 China School of Physics Science and Engineering Tongji University Shanghai200092 China School of Computer Science and Technology Zhejiang University of Water Resources and Electric Power Hangzhou310018 China Shenzhen Institute of Technology Innovation NIM Shenzhen518107 China College of Metrology and Testing Engineering China Jiliang University Hangzhou310018 China

The laser self-mixing grating interferometer based on Cr atom lithography gratings has been applied to the primary calibration of accelerometers due to its compact structure, low cost, high accuracy, and direct on-site traceability. However, the high line density of Cr gratings (4700 l/mm) introduces dense outliers in interferometric signals, complicating displacement demodulation via conventional derivative-based methods and causing frequent phase jumps. To address this challenge, we propose a hybrid algorithm integrating the continuous wavelet transform and the Hilbert transform, which enables robust displacement demodulation under high-noise conditions. Experimental validation on a commercial MEMS accelerometer demonstrated exceptional accuracy: 100 consecutive data segments were successfully demodulated with a displacement fitting goodness of R2 = 0.9964 (σR2 = 0.0027), and the derived sensitivity deviated by only 0.1% from the nominal value. This algorithm establishes a paradigm for the high-accuracy dynamic calibration of inertial sensors in field applications. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Accelerometers

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Industry 4.0 based Machine Learning Models for Anomalous Product Detection and Classification

Industry 4.0 based Machine Learning Models for Anomalous Pro...

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Sourabh Kumar Saroj Kumar Chandra Ram Narayan Shukla Lipismita Panigrahi Center of Excellence in Industry 4.0 Computer Science and Engineering OP Jindal University Raigarh India Department of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India

Automation has made tremendous changes in the industries. It has been used to automate the manual processes involved in different physical units of the industries. The purpose was to increase the production in the manufacturing. Now, computers are being used in the industries to monitor functionalities of different production units with the help of artificial intelligence and internet of things (IoT). The IoT has revolutionized the industries. It is an interconnected network system of physical units. The core purpose of it to gather and share information among different physical units. The IoT has great impact on the many areas such as business, industry, medicine, the economy, transport, industrial robots and automation systems. IoT with artificial intelligence has wide range of industrial applications. Industry 4.0 is used in the industries where different industrial units are connected over the internet and interacting to make decisions via machine-to-machine communication. It has increased the benefits of industries in terms of production and supply chain management. Manufacturing industry monitors its production units in every 10 milliseconds to capture features of the product that is being produced. The features generated in this process are huge in amount. Critical observation is performed on the generated features to categorize the product as anomalous or good. Product classification is difficult task in the labeled datasets due to human bias in labeling the final product as anomalous or good. In this work, machine learning models is being used to detect and classify faulty product produced by manufacturing industry. Both qualitative and quantitative study will be carried out to compare various machine learning models.

关键词： Manufacturing industries Biological system modeling Production Fourth Industrial Revolution Decision trees Biomedical monitoring Task analysis

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Projecting infinite time series graphs to finite marginal graphs using number theory

arXiv

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arXiv 2023年

作者： Gerhardus, Andreas Wahl, Jonas Faltenbacher, Sofia Ninad, Urmi Runge, Jakob German Aerospace Center Institute of Data Science Germany Technische Universität Berlin Institute of Computer Engineering and Microelectronics Germany

In recent years, a growing number of method and application works have adapted and applied the causal-graphical-model framework to time series data. Many of these works employ time-resolved causal graphs that extend infinitely into the past and future and whose edges are repetitive in time, thereby reflecting the assumption of stationary causal relationships. However, most results and algorithms from the causal-graphical-model framework are not designed for infinite graphs. In this work, we develop a method for projecting infinite time series graphs with repetitive edges to marginal graphical models on a finite time window. These finite marginal graphs provide the answers to m-separation queries with respect to the infinite graph, a task that was previously unresolved. Moreover, we argue that these marginal graphs are useful for causal discovery and causal effect estimation in time series, effectively enabling to apply results developed for finite graphs to the infinite graphs. The projection procedure relies on finding common ancestors in the to-be-projected graph and is, by itself, not new. However, the projection procedure has not yet been algorithmically implemented for time series graphs since in these infinite graphs there can be infinite sets of paths that might give rise to common ancestors. We solve the search over these possibly infinite sets of paths by an intriguing combination of path-finding techniques for finite directed graphs and solution theory for linear Diophantine equations. By providing an algorithm that carries out the projection, our paper makes an important step towards a theoretically-grounded and method-agnostic generalization of a range of causal inference methods and results to time series. Copyright © 2023, The Authors. All rights reserved.

关键词： Time series

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User Feedback Module for Women Self Help Group Chatbot for Increased Usability

User Feedback Module for Women Self Help Group Chatbot for I...

引用

Emerging Technology (INCET), International Conference for

作者： Moturi Karthikeya Sruthy Anand Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Center for Wireless Networks & Applications (WNA) Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

The recent advancement in AI and deep learning is revolutionizing various sectors, such as healthcare, education, and entertainment, to name a few. In this work, we explore the use of AI chatbots in rural digital empowerment and how AI chatbots can be utilized for supporting the small-scale businesses of rural self-help group members. The work explores the need for a user feedback module for a multi-lingual chatbot designed for a rural women's self-help group (SHGs) in India. Integration of the user feedback module will further enhance the usability and usefulness of the multi-lingual SHG chatbot. The work also examines the need for increased usefulness of the multi-lingual chatbot for improved adoption in SHGs. The work also emphasizes the need to design software based on the context of use considering the needs and objectives of the user group.

关键词： User-generated content Entertainment industry Oral communication Medical services Chatbots Software User experience

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AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations 22

AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and...

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22nd IEEE International Conference on Machine Learning and applications, ICMLA 2023

作者： Ganeriwala, Parth Bhattacharyya, Siddhartha Gunther, Sean Kish, Brian Khan, Mohammed Abdul Hafeez Dhadoti, Ankur Neogi, Natasha Florida Institute of Technology Dept. of Computer Science MelbourneFL United States Florida Institute of Technology Dept. of Aerospace Engineering MelbourneFL United States Univeristy of Michigan Dept. of Mechanical Engineering Ann ArborMI United States Bits Pilani Dept. of Computer Science Dubai Campus Dubai United Arab Emirates Langley Research Center Nasa HamptonVA United States

ISBN: (纸本)9798350345346

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. In this paper, we present AssistTaxi, a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Addition-ally, the dataset serves as a valuable resource for validating and enhancing existing algorithms, facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique. © 2023 IEEE.

关键词： aircraft perception autonomous driving computer vision dataset labeling line identification taxiway data

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Safe and Reliable Training of Learning-Based aerospace Controllers 43

Safe and Reliable Training of Learning-Based Aerospace Contr...

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43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024

作者： Mandal, Udayan Amir, Guy Wu, Haoze Daukantas, Ieva Newell, Fletcher Lee Ravaioli, Umberto Meng, Baoluo Durling, Michael Hobbs, Kerianne Ganai, Milan Shim, Tobey Katz, Guy Barrett, Clark Stanford University Center for Ai Safety Stanford United States School of Cs & Engineering The Hebrew University of Jerusalem Jerusalem Israel It University of Copenhagen Department of Computer Science Copenhagen Denmark Google Mountain View United States Ge Aerospace Research Niskayuna United States Us Air Force Air Force Research Laboratory Dayton United States Stanford University Department of Computer Science Stanford United States Stanford University Department of Data Science Stanford United States

ISBN: (纸本)9798350349610

In recent years, deep reinforcement learning (DRL) approaches have generated highly successful controllers for a myriad of complex domains. However, the opaque nature of these models limits their applicability in aerospace systems and sasfety-critical domains, in which a single mistake can have dire consequences. In this paper, we present novel advancements in both the training and verification of DRL controllers, which can help ensure their safe behavior. We showcase a design-for-verification approach utilizing k-induction and demonstrate its use in verifying liveness properties. In addition, we also give a brief overview of neural Lyapunov Barrier certificates and summarize their capabilities on a case study. Finally, we describe several other novel reachability-based approaches which, despite failing to provide guarantees of interest, could be effective for verification of other DRL systems, and could be of further interest to the community. © 2024 IEEE.

关键词： Deep reinforcement learning

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Human-centered Software Platform for Social Network of Self-Help Groups

Human-Centered Software Platform for Social Network of Self-...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Abhiram Bulusu Gudla Dinesh Reddy Vuppala Naga Sushanth Kumar Sruthy Anand Ramesh Guntha Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Center for Wireless Networks Applications (WNA) Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Designing user interfaces (UI) for marginalized rural women presents unique challenges that require a good understanding of Human-computer Interaction (HCI) principles to ensure usability. This research paper focuses on developing a contemporary UI for a social network of Self-Help Groups (SHGs) in India, catering to the diverse age groups and educational backgrounds within these communities. The goal is to blend HCI principles into the design to develop an interface that is attractive, user-friendly, and easy to navigate for the users of these communities. This study tries to employ a user-centered design thinking approach to guide the development of the UI prototype. The study details the use of financial module of the application and its implementation. The software utilizes a multi-level client-server architecture using Flutter frameworks for UI design.

关键词： Social networking (online) Navigation User centered design Prototypes Organizations Manuals Human factors Software User experience Usability

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