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Aerial Dockable Multirotor UAVs: design, Control, and Flight Time Extension Through In-Flight Battery Replacement

IEEE Access 2025年 13卷 96782-96799页

作者： Yeongin Song Hyunmin Kim Jeonghyun Byun Keun Park Murim Kim Seung Jae Lee Department of Mechanical Design and Robot Engineering Seoul National University of Science and Technology (SeoulTech) Seoul Republic of Korea Department of Aerospace Engineering Seoul National University Seoul Republic of Korea Human-Centered Robotics Research and Development Division Korea Institute of Robotics and Technology Convergence (KIRO) Pohang Republic of Korea

This paper presents the development and evaluation of the AirDock system, a novel aerial docking and in-flight battery exchange solution designed to extend the operational flight time of multirotor unmanned aerial vehicles (mUAVs). The proposed system enables seamless mid-flight battery replacement through an aerial docking mechanism and a rail-Car-based battery transfer and retrieval system. The AirDock platform utilizes a fully actuated multirotor design, allowing independent control of six degrees of freedom (DoF) motion to maintain a constant attitude during battery exchange operations, facilitating easy docking. In this research, a generalized control allocation algorithm is introduced to manage dynamic shifts in the center of mass (CoM) during inter-modular battery transportation, ensuring safe flight control and mitigating thruster overloading: a critical factor in avoiding flight failure. Both simulations and real-world experiments validate the system’s effectiveness, demonstrating stable aerial docking, reliable in-flight battery exchange performance, and extended flight durations for mission modules. These findings highlight the AirDock system’s potential to overcome the energy limitations of battery-powered UAVs, extending missions across various applications.

关键词： Batteries Propellers Propulsion Plugs Torque Hardware Robots Quadrotors Couplings Buildings

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Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1716-1729页

作者： Weiliang Zuo Jingmin Xin Changnong Liu Nanning Zheng Akira Sano IEEE the National Key Laboratory of Human-Machine Hybrid Augmented Intelligence the National Engineering Research Center for Visual Information and Applicationsand the Institute of Artificial Intelligence and RoboticsXi’an Jiaotong UniversityXi’an 710049China the Data Center China Construction BankBeijing 100033China the Department of System Design Engineering Keio UniversityYokohama 223-8522Japan

Despite some efforts and attempts have been made to improve the direction-of-arrival(DOA)estimation performance of the standard Capon beamformer(SCB)in array processing,rigorous statistical performance analyses of these modified Capon estimators are still *** paper studies an improved Capon estimator(ICE)for estimating the DOAs of multiple uncorrelated narrowband signals,where the higherorder inverse(sample)array covariance matrix is used in the Capon-like cost *** establishing the relationship between this nonparametric estimator and the parametric and classic subspace-based MUSIC(multiple signal classification),it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE,the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signal-to-noise ratio(SNR).Furthermore the statistical performance of the ICE is analyzed,and the large-sample mean-squared-error(MSE)expression of the estimated DOA is *** the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples,where the Cramer-Rao lower bound(CRB)is used to evaluate the validity of the derived asymptotic MSE expression.

关键词： Capon beamformer direction-of-arrival(DOA)estimation large-sample mean-squared-error(MSE) subspace-based methods uniform linear array

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Detection and Classification in Ballistic Drone Capturing Based on Transfer Learning Networks Using Infrared Images 6

Detection and Classification in Ballistic Drone Capturing Ba...

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6th IEEE Conference on Information and Communication Technology, CICT 2022

作者： Harsha Vardhan Reddy, M. Gothandaraman, Rajkumar Muthuswamy, Sreekumar Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Mechanical Engineering Chennai India Indian Institute of Information Technology Design and Manufacturing Center for Al IoT and Robotics Department of Mechanical Engineering Chennai Kancheepuram India

ISBN: (纸本)9781665473125

Unmanned aerial vehicles and drones are flying objects carrying small payloads for various applications, including agriculture, photography for weddings & religious ceremonies, e-commerce deliveries, remote sensing, 3D mapping, surveillance and defense. These flying objects also called as drones are available in two variants;1. Fixed wing propeller type, and 2. Multi-wings propeller type. Nowadays, UAVs and Drones are the primary threat to the national security on the mainland and the line of actual control. Generally, these threat-rising drones can be eradicated by anti-missile techniques, which are not economical however will destroy them. The objective of the work here is to design and develop a ballistic drone capturing system comprising two main steps;1. classification of UAVs from the flying birds and 2. Capturing the UAVs without causing significant damage to the drone. Here, the methodology uses computer-generated infrared images of the drone in the pretrained network architecture, which acts as the Convolution Neural Network (CNN) for classifying drones and birds. The performance of AlexNet and ResNet-50 performs better and it shows 100 percent efficiency and small distribution with more stability. In the near future, the ballistic capturing system will be designed and developed as a product, which would support acquiring data about malicious drones. © 2022 IEEE.

关键词： Drones

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Power Harvesting towards Sustainable Energy Technology through Ambient Vibrations and Capacitive Transducers

Power Harvesting towards Sustainable Energy Technology throu...

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2023 International Conference on Emerging Power Technologies, ICEPT 2023

作者： Jamil, Umar Sulaiman, Muhammad Ghafoor, Nouman Malmir, Mostafa Nawaz, Faisal Shakoor, Rana I. University of Texas at San Antonio Department of Electrical Engineering San Antonio United States Air University Department of Electrical Engineering Islamabad Pakistan University of Limerick Department of Science and Engineering Limerick Ireland Ajou University Department of Electrical Engineering Suwon Korea Republic of National Center of Robotics and Automation Air University Mems Sensor Design and Test Lab Islamabad Pakistan

ISBN: (纸本)9798350301014

As part of the fourth industrial revolution, low-power electronic devices require a power harvesting system to provide energy for their operation because energy harvesting technologies are crucial for enabling 90% of wireless sensor networks. While solar and thermal energy harvesting are popular methods, they have limitations such as dependence on sunlight and thermal gradients, which make them unreliable for low-wattage electronic equipment and wireless sensing networks. Power harvesting from ambient vibrations can lead to a sustainable system. Currently, there is a focus on different power harvesting principles such as electromagnetic, piezoelectric, and electrostatic. This research work presents a novel power harvester design that uses three in-plane capacitive transducers - gap-closing, overlap-varying, and pattern-varying - to operate under ambient vibrations as input energy. With low levels of input vibrations, the device moves, leading to changes in capacitance and the harvesting of reliable electrical power. The design analysis includes capacitance, frequency, and electromechanical evaluations to acquire capacitance matrices, natural frequencies for different modes, displacement covered by moving mass, charge distribution, and pressure distribution. © 2023 IEEE.

关键词： Energy harvesting

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Analysis and Characterization of Defects in FeFETs

Analysis and Characterization of Defects in FeFETs

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2023 IEEE International Test Conference, ITC 2023

作者： Thapar, Dhruv Thomann, Simon Chaudhuri, Arjun Amrouch, Hussam Chakrabarty, Krishnendu Duke University Department of Electrical and Computer Engineering North Carolina United States Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Arizona United States

ISBN: (纸本)9798350343250

Emerging devices are susceptible to manufacturing defects due to immature fabrication processes. Ferroelectric field-effect transistors, referred to as FeFETs, are promising emerging devices, but the impact of manufacturing imperfections on these devices has yet to be studied. Thus, we combine a technology CAD (TCAD) model with a fault-injection technique to represent fabrication defects in a FeFET. The TCAD model is calibrated against a fabricated metal-ferroelectric-metal capacitor and uses a multi-domain ferroelectric-layer structure. We address two classes of defects in the ferroelectric layer and map them to stuck-at-fault models referred to as neutral faults (SAP°) and stuck-at-plus and stuck-at-minus (SAP+ and SAP-) faults. We also develop a machine-learning (ML) framework to characterize these fault-injected FeFET devices. The ML framework provides a significant speedup in predicting the health of the FE layer as compared to computationally heavy TCAD simulations. Our study of defects in ferroelectric FET (FeFET), which is done for the first time, and the insights gained thereof can provide valuable feedback for the fabrication and yield learning of FeFET-based circuits. © 2023 IEEE.

关键词： Defects

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Suppression of thermal transport in bent boron arsenide nanoribbons

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Physical Review Applied 2024年第5期22卷 054019页

作者： Guanbo Jiao Shuo Qiao Jun Lyu Yi Tao Lin Yang Department of Advanced Manufacturing and Robotics College of Engineering School of Mechanical Engineering and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments National Key Laboratory of Advanced Micro and Nano Manufacture Technology

Boron arsenide (BAs) has emerged as a strong contender for next-generation functional materials, boasting desirable attributes such as high thermal conductivity and ambipolar mobility. However, a critical yet underexplored challenge lies in understanding its heat conduction capabilities under inhomogeneous strain, which is pivotal across various functional devices and operational conditions. Here, through modeling thermal transport in bent BAs and Si nanoribbons, a striking difference is revealed. Namely, the BAs nanoribbons exhibit nearly twice the reduction in thermal conductivity compared with Si under identical bending conditions. This significant disparity is driven by two key factors: the pronounced effect of phonon-spectra broadening under strain and the inhomogeneous strain-induced narrowing of the acoustic and optical (ao) gap. Together, these factors relax the originally restricted phonon scattering phase space and fundamentally alter phonon scattering dynamics. Our findings not only offer a new perspective on how heat transfer can be dynamically modulated in BAs, but also provide crucial insights into enhancing thermal performance in BAs-based functional devices.

关键词： Anharmonic lattice dynamics Bending Heat transfer Phonons Strain Thermal conductivity Nanoribbon Molecular dynamics

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An Open Framework for Smart Retrofitting of Legacy Industrial Machines Towards Industry 4.0

An Open Framework for Smart Retrofitting of Legacy Industria...

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IEEE Region 10 International Conference TENCON

作者： Deep Patel Sreekumar Muthuswamy Department of Mechanical Engineering Centre for AI IoT and Robotics Design and Manufacturing Indian Institute of Information Technology Chennai India

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

This paper presents a six-layer framework for smart retrofitting of legacy industrial machines to align with Industry 4.0 standards, using open-source technologies for cost-effectiveness and scalability. The layers include edge data acquisition, data preprocessing, Digital Twin technology, long-term data storage, AI-based data analysis, and real-time visual-ization. Implemented and evaluated through a case study on a legacy CNC lathe, the framework demonstrated reliable communication and effective performance across various layers. The results validate the framework's feasibility and highlight the need for further fine-tuning of open large language models with manufacturing domain knowledge.

关键词： Scalability Large language models Data preprocessing Memory Real-time systems Fourth Industrial Revolution Digital twins Reliability Standards IEEE Regions

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Functional Materials and Innovative Strategies for Wearable Thermal Management Applications

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Nano-Micro Letters 2023年第9期15卷 562-603页

作者： Yeongju Jung Minwoo Kim Taegyeom Kim Jiyong Ahn Jinwoo Lee Seung Hwan Ko Applied Nano and Thermal Science Lab Department of Mechanical EngineeringSeoul National University1 Gwanak-roGwanak-guSeoul 08826South Korea Department of Mechanical Roboticsand Energy EngineeringDongguk University30 Pildong-ro 1-gilJung-guSeoul 04620South Korea Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National UniversityGwanak-roGwanak-guSeoul 08826South Korea Institute of Engineering Research Seoul National University1 Gwanak-roGwanak-guSeoul 08826South Korea

Thermal management is essential in our body as it affects various bodily functions,ranging from thermal discomfort to serious organ failures,as an example of the worst-case *** have been extensive studies about wearable materials and devices that augment thermoregulatory functionalities in our body,employing diverse materials and systematic approaches to attaining thermal *** paper reviews the recent progress of functional materials and devices that contribute to thermoregulatory wearables,particularly emphasizing the strategic methodology to regulate body *** exist several methods to promote personal thermal management in a wearable *** instance,we can impede heat transfer using a thermally insulating material with extremely low thermal conductivity or directly cool and heat the skin ***,we classify many studies into two branches,passive and active thermal management modes,which are further subdivided into specific *** from discussing the strategies and their mechanisms,we also identify the weaknesses of each strategy and scrutinize its potential direction that studies should follow to make substantial contributions to future thermal regulatory wearable industries.

关键词： Thermal management Passive heat transfer Active heat transfer Wearable materials Wearable device

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Development of a Flexible Magnetic Multi-Arm Robot for Ceiling Inspection

Development of a Flexible Magnetic Multi-Arm Robot for Ceili...

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SICE Annual Conference

作者： Jer Luen Chien Shawndy Michael Lee Mario Josue Perez Cruz Shaohui Foong Photchara Ratsamee Engineering Product Development (EPD) Pillar of Singapore University of Technology and Design (SUTD) Singapore Department of Robotics and Systems Design Osaka Institute of Technology Osaka Japan

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

Continuum robots have the capability to perform flexible locomotion for navigation through tortuous paths. In this paper, we propose a multi-arm robot with multiple flexible tendon-driven continuum robots with magnets to demonstrate how compliance can be used to navigate through difficult environments. Furthermore, we propose an extended mathematical model from the Cosserat rod model to solve for the inverse kinematics of the robot to use motor displacements as inputs for robot control. We show an initial prototype of our system, and demonstrate the proposed robot's movement with an obstacle avoidance and an u-shaped locomotion experiment.

关键词： Navigation Robot control Prototypes Inspection Motors Manipulators Mathematical models Continuum robots Magnets Robots

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Real-Time Identification of Plant Diseases Using Aerial Robots and Deep Learning Techniques

Real-Time Identification of Plant Diseases Using Aerial Robo...

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International Conference on Advanced robotics (ICAR)

作者： Prajwal Maski Siddhant Panigrahi Abhinav Azad Asokan Thondiyath Robotics Lab IIT Madras Department of Engineering Design IIT Madras Tamil-Nadu India

Agriculture is of paramount importance in providing sustenance to human populations globally. It is a crucial economic growth driver, particularly in emerging nations like India, where majority of the people depend on it. However, the proliferation of plant diseases and pests presents significant threats, leading to substantial declines in crop productivity and agricultural losses. In this regard, real-time identification of plant-based diseases and pests can revolutionise plant monitoring, leading to more efficient and targeted interventions. Hence, in this current research, we present the methodology for performing real-time plant disease detection using lighter versions of deep learning algorithms implemented on sample payloads of mobile robots. Unlike literature that utilises high-end sensors for image acquisition, this study uses off-the-shelf sensors to build an embedded platform and tests the proposed methodology in real-time field surveys. Field studies demonstrate that such a fabricated platform is able to characterise not only the disease but also identify its associated stages with a Mean Average Precision (mAP) of ≈ 96% within 6000 training iterations, achieving a detection speed of 6-10 FPS. We claim using such mobile platform setups can help in effective crop surveillance and timely pest management.

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