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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Ding, Menglong Xie, Anhuan Zhu, Shiqiang Song, Wei Cai, Jiandong Yan, Xufei Zhao, Pengyu Gu, Jason Zhang, Yanyan Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H4R2 Canada

ISBN: (纸本)9781665481090

The emergence of electric Vertical Takeoff and Landing (eVTOL) aircraft makes cheap, quiet and reliable short-range flights possible. As a manned aircraft, eVTOL's occupant protection capability is critical and its crashworthiness must be improved via optimization of energy absorption design for structures. This study aims to evaluate the crashworthiness of composite components and the entire eVTOL structure within the design space via the building-block approach. A variety of designs for the skid landing gear, energy absorber, structures in the cockpit and the combination of them were estimated by using the numerical method. The results show a tremendous reduction in occupant injury risk with the optimization of the skid landing gear, energy absorber and the entire eVTOL structure. This work provides a preliminary optimization design and evaluation methodology of crashworthiness for an eVTOL. © 2022 IEEE.

关键词： Crashworthiness

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PDAVIS: Bio-inspired Polarization Event Camera

PDAVIS: Bio-inspired Polarization Event Camera

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Haessig, Germain Joubert, Damien Haque, Justin Milde, Moritz B. Delbruck, Tobi Gruev, Viktor Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria University of Zurich Institute of Neuroinformatics ETH Zurich Switzerland Western Sydney University International Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States

ISBN: (纸本)9798350302493

The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical ***: https://***/mFuCeTMWEqY © 2023 IEEE.

关键词： Polarization

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Temporal Sensitivity Analysis of Internal Temperature Informed Charging Algorithms and Rapid Thermal Management System for E-mobility

Temporal Sensitivity Analysis of Internal Temperature Inform...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Akash Samanta Chandan Chetri Dominic Karnehm Antje Neve Sheldon Williamson Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada Institute of Intelligent Distributed Systems Bundeswehr University Munich Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

The experimental studies presented in this paper reveal that existing thermal management systems (TMS) and temperature-informed charging algorithms exhibit a response time lag of at least 5.3 minutes due to their reliance on surface temperature measurements. The results indicate that changes in the internal thermal state of lithium-ion batteries (LIBs), induced by variations in charging currents, take an average of 2 minutes to manifest on the battery surface, particularly evident in cylindrical cells. Current thermal management systems for automotive battery packs solely rely on surface temperature measurements, neglecting the approximately 5.8°C temperature difference between the core and surface in TMS control. Consequently, changes in the battery's thermal state due to internal heat losses are not promptly detected by surface-mounted temperature sensors. This delayed response time accelerates battery degradation and increases the risk of thermal runaway events. In this study, temperature-informed fast charging algorithms, tested under various ambient conditions for LIBs, along with a comparative analysis, demonstrate that response time can be reduced by at least 2 minutes by considering internal temperature rather than relying solely on surface temperature measurements. Moreover, accounting for the temperature difference between the core and surface facilitates rapid TMS control and health-conscious fast charging, thereby mitigating the risk of thermal runaway events.

关键词： Temperature measurement Temperature sensors Heating systems Sensitivity analysis Surface charging Thermal management Time measurement Fast charging Time factors Thermal degradation

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Aerodynamic Simulation of a Typical Multirotor e VTOL Aircraft Configuration

Aerodynamic Simulation of a Typical Multirotor e VTOL Aircra...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Ding, Menglong Zhang, Yanyan Zhu, Shiqiang Song, Wei Zhao, Pengyu Yan, Xufei Cai, Jiandong Gu, Jason Xie, Anhuan Research Institute of Interdisciplinary Innovation Zhejiang Lab Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H4R2 Canada

ISBN: (纸本)9781665481090

The aerodynamic interaction among rotors is a key phenomenon that influences the performance of the electric Vertical Takeoff and Landing (eVTOL) aircraft. This study applied Lattice-Boltzmann Method (LBM) to systematically investigate the aerodynamic interaction under typical flight conditions. Simulation of a single rotor was performed to validate the reliability of LBM on rotor aerodynamics and find the maximum acceptable grid size. A numerical study on the complex unsteady flowfield caused by the sixteen rotors was also performed when considering the eVTOL is in hovering, forward flight and hovering under sidewind. Moreover, the analysis of the flowfield provides a detailed insight into the flow physics involved in such regular flight conditions. © 2022 IEEE.

关键词： VTOL/STOL aircraft

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Distributed Optimization via Gradient Descent with Event-Triggered Zooming Over Quantized Communication

Distributed Optimization via Gradient Descent with Event-Tri...

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IEEE Conference on Decision and Control

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA US Department of Electrical and Computer Engineering School of Engineering University of Cyprus Aalto University Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technologyy Stockholm Sweden

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples.

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How to Swarm: Entropy-Based Model Parameter Analysis

How to Swarm: Entropy-Based Model Parameter Analysis

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IEEE Southeastcon

作者： Nathan Rayon Stefan Wheeless Gabriel Broom Hakki Erhan Sevil Department of Computer Science University of West Florida (UWF) Pensacola FL USA Department of Electrical and Computer Engineering University of West Florida (UWF) Pensacola FL USA Department of Intelligent Systems and Robotics University of West Florida (UWF) Pensacola FL USA

In this study, we implemented our entropy-based swarm model to an autonomous waypoint navigation application for a group of multi-rotor Unmanned Aerial Vehicles (UAVs) through a set course in free space. Multi-UAVs of multiple group sizes were run with variations in parameters, and the path lengths traveled were measured to determine the most efficient configurations, and we investigated the impact of varying parameters on the swarm behavior performance. The simulation of the UAV kinematics and environment was performed in AirSim. The results show that the swarm model with different parameter setup operates successfully and the effects of the parameter selection on our multi-UAV swarm model are discussed.

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Efficient Prediction of Admittance of Inverter-Based Resources Across Operating Points: A Comprehensive Test

Efficient Prediction of Admittance of Inverter-Based Resourc...

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IEEE General Meeting Power& Energy Society

作者： Jaleel Mesbah Jingzhe Xu Weihua Zhou Behrooz Bahrani Sushrut Thakar Stavros Konstantinopoulos Deepak Ramasubramanian Mobolaji Bello Department of Electrical and Computer Systems Engineering Monash University Melbourne Australia Power Delivery and Utilization Electric Power Research Institute Knoxville USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

This paper presents a comprehensive comparative study of two admittance prediction algorithms—data-driven and analytical—applied to Inverter-Based Resources (IBRs). The performance of these algorithms is compared using a set of white-box IBR models, with the same training and test points employed for both to ensure a consistent basis for comparison. The study evaluates the effectiveness of these methods in accurately predicting the admittance of IBRs, emphasizing the influence of Operating Point (OP) variations on prediction accuracy. Performance evaluation is conducted through a "goodness of fit" metric. Additionally, this paper conducts a sensitivity analysis of the Analytical Prediction Method (APM), examining its adaptability across different control structures and parameters. Ultimately, this paper validates the APM using a generic black-box model, underlining its applicability and potential in real-world scenarios.

关键词： Training Sensitivity analysis Closed box Training data Prediction methods Power system stability Prediction algorithms Stability analysis Admittance Inverter-based resource

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A Novel Bayesian Optimization Framework for RIS-Assisted Wireless Networks

A Novel Bayesian Optimization Framework for RIS-Assisted Wir...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Charles Ross Gabriele Gradoni Zhen Peng Electrical and Computer Engineering Department University of Illinois at Urbana-Champaign IL USA Institute for Communication Systems University of Surrey Surrey Guildford UK

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

Reconfigurable Intelligent Surface (RIS) emerges as a promising technology for shaping the wireless propagation environment. In this paper, we introduce a novel Bayesian optimization framework to address the challenge of joint channel estimation and optimization in complex wireless environments. To reduce the dimensionality of large-scale RIS, the framework incorporates a unique physics-informed structure embedding utilizing angular and spatial domain basis vectors. We validate our approach through laboratory experiments conducted with software-defined radio equipment, considering scenarios where the receivers are located in near-field or far-field regions. The results demonstrate superior channel gain per iteration compared to existing methods.

关键词： Wireless sensor networks Wireless networks Channel estimation Receivers Reconfigurable intelligent surfaces Vectors Bayes methods

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Safe residual reinforcement learning for helicopter aerial refueling

Safe residual reinforcement learning for helicopter aerial r...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Damsara Jayarathne Santiago Paternain Sandipan Mishra Department of Mechanical Aerospace and Nuclear Engineering of Rensselaer Polytechnic Institute Troy NY Department of Electrical Computer and Systems Engineering of Rensselaer Polytechnic Institute Troy NY

Autonomous helicopter aerial refueling is a challenging problem because of the complex aerodynamic interactions between the helicopter, the tanker and the refueling hose-drogue system. Methodologies solely relying on model-based control approaches are unable to directly address the aerodynamic interactions, whereas pure data-driven methods such as reinforcement learning (RL) often do not provide safety guarantees. Therefore, in this paper, we propose a novel residual RL control methodology that works in conjunction with a model-based outer-loop position controller. Further, we incorporate a safe RL algorithm that assures probabilistic safety guarantees by imposing appropriate constraints. This algorithm leverages the primal-dual formulation of a constrained optimal control problem to solve a sequence of RL problems that ultimately guarantees a probabilistic safety assurance requirement. The RL agent is trained in a simulation platform that consists of a reduced-order helicopter model and a state-dependent control mixer that appropriately delegates the control authority between the outer-loop controller and the RL controller. Once trained, the RL agent is deployed on a physics-based high-fidelity helicopter model without additional parameter tuning. These high-fidelity simulations reveal that the application of the proposed methodology yields a mean 2-norm error of 0.25m at the time of docking, which outperforms a purely model-based controller by 24%.

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Emergency Clinical Procedure Detection via Wearable Sensors

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2022年第1期66卷 2239 - 2243页

作者： Prakash Baskaran Jamison Heard Julie A. Adams Collaborative Robotics and Intelligent Systems Institute Oregon State University Corvallis OR Department of Electrical and Microelectronic Engineering Rochester Institute of Technology NY

Communicating a patient’s state accurately during transfer from emergency medical technicians to hospital personnel is crucial for optimal care. Prior work demonstrated automated algorithms that combined wearable sensors with video data from cameras to detect clinical procedures and improve this information transfer. However, incorporating video requires task-or environment-specific installation mechanisms, raises privacy concerns, and is susceptible to occlusion and image noise. The presented approach detects clinical procedures using wearable sensors (i.e., inertial and electrophysiological) only and the procedures’ subtasks to mitigate the sensors’ signal variability to provide clinical procedure detection.

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