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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Pereira, Jorge Mendes, Jerome Junior, Jorge S. S. Viegas, Carlos Paulo, Joao Ruivo University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Pólo Ii CoimbraPT-3030-290 Portugal University of Coimbra Association for the Development of Industrial Aerodynamics CoimbraPT-3030-289 Portugal

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Every year, wildfires cause significant losses and destruction around the globe. In order to attempt to reduce their damages, resources have been put into developing fire propagation prediction systems. In a real wildfire event, these systems provide the authorities with information about the fire propagation in the near future, thus allowing them to make better decisions. Wildfire spread prediction systems are based on fire propagation models, from which the most used and accepted model is the Rothermel model. However, given the complexity of the wildfire phenomena and the uncertainty of some of its input parameter values, the Rothermel model can produce misleading results of fire propagation. This paper uses 3 metaheuristic algorithms, genetic algorithm (GA), differential evolution (DE) and simulated annealing (SA), for calibration of input parameters from the Rothermel model. These algorithms were validated using 37 datasets containing data from controlled experimental fires. Results have shown that these algorithms provide a precise wildfire spread prediction accounting for the uncertainties in the model's selected parameters. © 2022 IEEE.

关键词： Forecasting

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A Study of Noise Reduction Algorithm Using Statistical Optimization in Digital Holographic Microscopy

A Study of Noise Reduction Algorithm Using Statistical Optim...

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International Joint Conference on Computer Science and Software engineering (JCSSE)

作者： Jongpil Jeong Hyun–Woo Kim Myungjin Cho Min–Chul Lee Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan School of ICT Robotics and Mechanical Engineering IITC. Hankyong National University Anseong Kyonggi-do Republic of Korea

ISBN: (数字)9798350381764

ISBN: (纸本)9798350381771

Recently, due to the coronavirus era, we have a heightened need for fast and accurate diagnostics. To meet these requirements, there are many methods such as polymerase chain reaction, but they also require about from a few hours to a day. In contrast, a three-dimensional model of cells can be observed by simply extracting cells and photographing them with digital holographic microscopy, and in the case of diseases that can be classified b y t he shape of cells, diagnosis i s possible in a few minutes. However, there are precise focal issues and noise in the high-frequency domain, respectively. Therefore, to resolve these issues, we propose an optimization method by modifying the threshold value of the high variance pixel averaging method in digital holographic microscopy.

关键词： Gamma distribution Visualization Three-dimensional displays Shape Microscopy Noise Noise reduction

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Online Learning in Blockchain-based Energy Trading systems 24

Online Learning in Blockchain-based Energy Trading Systems

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2024 International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2024

作者： Liu, Yunshu Cheung, Man Hon Huang, Jianwei Pillar of Engineering Systems and Design Singapore University of Technology and Design Singapore Singapore Department of Computer Science City University of Hong Kong Hong Kong School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network CSIJRI Joint Research Centre on Smart Energy Storage The Chinese University of HongKong Guangdong Shenzhen518172 China

ISBN: (纸本)9798400705212

In this paper, we consider a blockchain-based energy trading (BBET) system with the proof-of-stake (PoS) protocol. The system designer aims to minimize system cost by considering the prosumers’ strategic token allocation between blockchain staking and energy purchase for their applications. This is challenging as the system designer does not know prosumers’ private information of impatience levels towards different applications. To this end, we propose an online learning mechanism (OLM), which includes incentive mechanisms to guide both prosumers’ private information reporting and staking decisions in two phases. In the exploration phase, we design a randomized staking reward to encourage prosumers’ truthful reporting of their private information for the learning of impatience level distributions. Based on the threshold structure of the prosumers’ equilibrium staking strategies, in the exploitation phase, we propose a learning-error-based reward to minimize the system cost considering the finite-sample bias. By characterizing the optimal exploration duration, we prove that OLM achieves an asymptotic zero-regret against the complete information benchmark, with the regret bounded by O(3√lnT/T) when operating for T time slots. We implement the corresponding smart contract in Ethereum to demonstrate the feasibility of our approach. Experiment results show that our mechanism reduces regret by an average of 74% compared to the state-of-art mechanism. © 2024 Copyright held by the owner/author(s).

关键词： Blockchain

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Automated Microrobotic Manipulation with Micron-scale Precision Using Multimodal Magnetic Microswarms

Automated Microrobotic Manipulation with Micron-scale Precis...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Jiang, Jialin Yang, Lidong Zhang, Li The Chinese University of HongKong Department of Mechanical and Automation Engineering Hong Kong Hong Kong Department of Industrial and Systems Engineering China The Chinese University of Hong Kong Department of Surgery Hong Kong The Chinese University of Hong Kong Cuhk T Stone Robotics Institute Hong Kong Hong Kong The Chinese University of Hong Kong Chow Yuk Ho Technology Center for Innovative Medicine Hong Kong Hong Kong Science Park Multi-Scale Medical Robotics Center China

ISBN: (纸本)9798350327182

Untethered microrobots possess a promising perspective for micro-manipulation applications. With specifically designed morphologies and structures, microrobots are able to perform controllable delivery of target objects. However, the manipulation process still lacks autonomy, the picking, transporting, and releasing behaviors of microrobots need analysis. In this paper, we propose to achieve automated microrobotic manipulation with multimodal magnetic microswarms. The microswarm is composed of numerous Fe3O4 nanoparticles. When exposed to different dynamic magnetic fields (rotating magnetic field and oscillating magnetic field), the swarm could exhibit corresponding forms and generate attracting and repelling effects for micro-objects, respectively. Exploiting these two types of swarms, precise and controllable picking and releasing can be realized. The manipulation process is quantitatively divided into five stages, and a finite state machine (FSM) is presented to govern the transition between the stages. To guarantee accurate motion control of the swarm, a disturbance observer (DOB)-based super-twisting sliding mode control (STSMC) is designed. Experiments are conducted to validate the feasibility of the proposed manipulation scheme. The results demonstrate that the swarm is capable of automatically and effectively delivering micro-cargoes with different sizes to the target positions. © 2023 IEEE.

关键词： Magnetite

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vPlanSim: An Open Source Graphical Interface for the Visualisation and Simulation of AI systems 31

vPlanSim: An Open Source Graphical Interface for the Visuali...

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31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Roberts, Jamie O. Mastorakis, Georgios Lazaruk, Brad Franco, Santiago Stokes, Adam A. Bernardini, Sara School of Engineering Institute for Integrated Micro and Nano Systems University of Edinburgh United Kingdom EPSRC CDT in Robotics and Autonomous Systems Edinburgh Centre for Robotics United Kingdom Department of Computer Science Royal Holloway University of London United Kingdom

ISBN: (纸本)9781713832317

We introduce vPlanSim, an open source tool to aid in AI PDDL development. This tool is primarily aimed at researchers and developers who need a visual representation of their planning problem so that they can make useful insights into the performance of their system, and also to naturally convey their system to others. It is an open-source tool which allows a user to quickly and easily visualise a target environment to generate the problem files and also to visualise a plan. It is particularly well suited to spatial planning problems. This paper will demonstrate vPlanSim on 2D and 3D planning problems. vPlanSim is based on a small and carefully considered set of dependencies such as VTK and PyQt. It can be set up on different platforms and compiled from source with minimal effort. The code is and maintained via a clear code review mechanism. We welcome contributions from the open-source community. Copyright © 2021, Proceedings of the 31st International Conference on Automated Planning and Scheduling. All rights reserved.

关键词： Open systems

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Robust tube-based LPV-MPC for autonomous lane keeping

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IFAC-PapersOnLine 2022年第35期55卷 103-108页

作者： Maryam Nezami Hossam Seddik Abbas Ngoc Thinh Nguyen Georg Schildbach Institute for Electrical Engineering in Medicine University of Lübeck Lübeck Germany Institute for Robotics and Cognitive Systems University of Lübeck Lübeck Germany

This paper proposes a control architecture for autonomous lane keeping by a vehicle. In this paper, the vehicle dynamics consist of two parts: lateral and longitudinal dynamics. Therefore, the control architecture comprises two subsequent controllers. A longitudinal model predictive control (MPC) makes the vehicle track the desired longitudinal speeds that are assumed to be generated by a speed planner. The longitudinal speeds are then passed to a lateral MPC for lane keeping. Due to the dependence of the lateral dynamics on the longitudinal speed, they are represented in a linear parameter-varying (LPV) form, where its scheduling parameter is the longitudinal speed of the vehicle. In order to deal with the imprecise information of the future longitudinal speed (the scheduling parameter), a bound of uncertainty is considered around the nominal trajectory of the future longitudinal velocities. Then, a tube-based LPV-MPC is adopted to control the lateral dynamics for attaining the lane keeping goal. In the end, the effectiveness of the proposed methods is illustrated by carrying out simulation tests.

关键词： Automotive Dynamic Uncertain systems LPVS Predictive Control Optimal Control Robustness Issues

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Self-Organized Sensor Eggs for Decentralized Localization and Sensing on Vulcano Island – A Glimpse into Future Space Exploration with Swarms

Self-Organized Sensor Eggs for Decentralized Localization an...

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International Conference on Information Fusion

作者： Fabio Broghammer Thomas Wiedemann Siwei Zhang Armin Dammann Christian Gentner Petar Djuric Institute of Communications and Navigation German Aerospace Center (DLR) Germany Perception for Intelligent Systems Munich Institute of Robotics and Machine Intelligence TU Munich Germany Department of Electrical and Computer Engineering Stony Brook University USA

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Robotic swarms or portable sensor networks are emerging technologies for sensing physical processes that are spatially distributed- and temporally dynamic, both on Earth and in future Moon/Mars exploration missions. We develop a portable network composed of a multitude of self-organized “sensor eggs”. These eggs are equipped with ultra-wideband (UWB) transceivers, providing precise time and position information without additional infrastructures like Global Navigation Satellite systems (GNSSs). Each egg is additionally equipped with environmental sensors, for example, a Sulfur dioxide gas sensor to explore volcanic activity. We use a real time decentralized particle filter (DPF) to estimate the a-posteriori probability density functions (PDFs) of the egg positions. These PDFs are then used in a static state binary Bayes filter for estimating the gas sources with potentially complex structures such as cracks on the volcano surface. The proposed sensor network is verified with an in-field experiment at La Fossa volcano on the island of Vulcano, Italy, in 2023.

关键词： Location awareness Volcanic activity Probability density function Robot sensing systems Particle filters Transceivers Sensors Timing Surface cracks Ultra wideband technology

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Analytical Model Transfer-Based Surrogate-Assisted Design Optimization for SPMVM Using Structural Similarity 26

Analytical Model Transfer-Based Surrogate-Assisted Design Op...

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26th International Conference on Electrical Machines and systems, ICEMS 2023

作者： Liu, Liyang Ma, Yiming Wang, Ruichi Li, Zequan Xiao, Yang Zhao, Hang Robotics and Autonomous Systems Thrust Guangzhou China CSG PGC Energy Storage Research Institute China Southern Power Grid Energy Storage Co. Ltd Guangzhou China Loughborough University The Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough United Kingdom Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China

ISBN: (纸本)9798350317589

This paper proposes an efficient surrogate-assisted design optimization method for a surface-mounted permanent-magnet vernier machine (SPMVM) based on subdomain model transfer learning. In the design optimization of SPMVM with parallel slot structure with asymmetric circumferential structure, a fictitious motor model with similar structure and identical parameters except for the parallel tooth structure is created. This fictitious motor with symmetric circumferential structure is used to build a subdomain model, so that a high-precision surrogate model can be built for optimization with the aid of analytic model data to reduce the size of the finite element dataset required for the training process, and accelerate the optimization process. © 2023 IEEE.

关键词： Permanent magnets

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Producing Lunar Steel and Oxygen using Molten Lunar Regolith Electrolysis

Producing Lunar Steel and Oxygen using Molten Lunar Regolith...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2023

作者： Patel, Palak B. Soto, Jose Adams, Zachary K. Koller, Scarlett Latyshev, Kir Boothe, Evan Cooper, Amber Fontanez, Jonatan Jalil, Laman Ma, Beverly Meza, Cesar Misquitta, Kristoff Na, Hyein Nguyen, Tom Pendley, Hezekiah Sangabattula, Lokesh Usey, Helena Zehner, Alice Allanore, Antoine Culpepper, Martin De Weck, Olivier Lordos, George Hoffman, Jeffrey Bergman, Dean Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology Sloan School of Management CambridgeMA02139 United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Material Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Honeybee Robotics Exploration Systems AltadenaCA91001 United States

ISBN: (纸本)9781624107054

With the current Artemis missions planned, by 2028, NASA and its international and commercial partners may be establishing a permanent presence at the lunar South pole. The Artemis Base Camp will be the locus of international and public-private collaboration under the Artemis Accords, helping to bootstrap a lunar economy. As the lunar economy grows, traffic of people and goods will grow with it. Thus, we envision that NASA and its international and commercial partners will have increasing long-term needs for producing metal from in situ resources such as lunar regolith. These metals can be used to produce many end products on the moon including large pressure vessels, both for spacious habitats and industrial-scale storage and operations. In this paper, as a part of the NASA 2023 BIG Idea Challenge ‘Lunar Forge: Producing Metal Products on the Moon’, we design and manufacture a molten regolith electrolysis (MRE) reactor capable of producing various alloys of steel and other metal products from lunar regolith, with oxygen as a useful byproduct. We have built ARTEMIS Steelworks (Advancing Reactor Technologies for Electrolytic Manufacturing of In situ Steel), which consists of an electrolytic reactor, supporting the addition of alloying elements to produce molten steel from lunar regolith simulant. To prepare for a lunar technology demonstration, a preliminary test of the reaction on Earth was performed in a vacuum, a sonicator was tested to dislodge oxygen bubbles from the anode to increase electrode life, and an automated iron and slag collector was made to reduce the need for astronaut operation. The project’s technical objectives are to demonstrate steel-making capability while also quantifying energy efficiency, steel quality, and the expected useful life of the electrodes and vessel under different configurations relative to the state of the art. The comprehensive testing plan presented here includes functional subsystem and integrated testing in ambient conditio

关键词： Electrolysis

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Autonomous Building of Structures in Unstructured Environments via AI Planning 31

Autonomous Building of Structures in Unstructured Environmen...

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31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Roberts, Jamie O. Franco, Santiago Stokes, Adam A. Bernardini, Sara School of Engineering Institute for Integrated Micro and Nano Systems University of Edinburgh United Kingdom EPSRC CDT in Robotics and Autonomous Systems Edinburgh Centre for Robotics United Kingdom Department of Computer Science Royal Holloway University of London United Kingdom

ISBN: (纸本)9781713832317

In this paper, we offer a novel AI planning representation, based on a Cartesian coordinate system, for enabling the autonomous operations of Multi-Robot systems in 3D environments. Each robot in the system has to conform to unique actuation and connection constraints that create a complex set of valid configurations. Our approach allows Multi-Robot systems to self-assemble themselves into larger structures via AI planning, with the overarching goal of providing structural capabilities in harsh and uncertain environments. In comparing four different PDDL (Planning Domain Definition Language) domain representations, we show that our novel formulation satisfies the practical requirements emerging from robot deployment in the real world, resulting in an AI planning system that is accurate and efficient. We scale up performance by implementing direct FDR (Finite Domain Representation) generation based on the best performing PDDL model, bypassing the PDDL-to-FDR translation used by the majority of modern planners. The proposed approach is general and can be applied to a broad range of AI problems involving reasoning in 3D spaces. Copyright © 2021, Proceedings of the 31st International Conference on Automated Planning and Scheduling. All rights reserved.

关键词： Multipurpose robots

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