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IEEE International Symposium on Information Theory

作者： Anatoly Khina Neri Merhav Department of Electrical Engineering-Systems Tel Aviv University Tel Aviv Israel Viterby Faculty of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

The problem of transmitting a parameter value over an additive white Gaussian noise (AWGN) channel is considered, where, in addition to the transmitter and the receiver, there is a helper that observes the noise non-causally and provides a description of limited rate $R_{\mathrm{h}}$ to the transmitter and/or the receiver. We derive upper and lower bounds on the optimal achievable $\alpha-\mathbf{th}$ moment of the estimation error and show that they coincide for small values of $\alpha$ and for high values of $R_{\mathrm{h}}$ . The upper bound relies on a recently proposed channel-coding scheme that effectively conveys $R_{\mathrm{h}}$ bits essentially error-free and the rest of the rate—over the same AWGN channel without help, with the error-free bits being allocated to the most significant bits of the quantized parameter.

关键词： AWGN channels Estimation error Upper bound Transmitters Noise Receivers Information theory

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A Design and Implementation of Water Heater Model Plant with Temperature Estimation Model for IOT Studies 7

A Design and Implementation of Water Heater Model Plant with...

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7th International Conference on Vocational Education and electrical engineering, ICVEE 2024

作者： Pradhana, Anak Agung Surya Funabiki, Nobuo Kotama, I Nyoman Darma Desnanjaya, I Gusti Made Ngurah Radhitya, Made Leo Mahajaya, Nyoman Sarasuartha Okayama University Graduate School of Environmental Life Natural Science and Technology Okayama Japan Okayama University Department of Electrical and Communication Engineering Okayama Japan Institute of Business and Technology Indonesia Department of Computer System Engineering Denpasar Indonesia Institute of Business and Technology Indonesia Department of Informatic Technology Denpasar Indonesia Institut Teknologi Dan Bisnis Stikom Departement of Magister Information Systems Denpasar Indonesia

ISBN: (纸本)9798331505103

This study presents the development of an Internet of Things (IoT) system for a water heater model, focusing on enhancing reliability during sensor malfunctions that could disrupt operations. Using the SEMAR IoT platform, the system efficiently collects and analyzes data, while the integration of the Holt-Winter algorithm ensures accurate temperature estimates, even with unreliable or missing sensor data. The algorithm successfully auto-calibrates sensors, predicts temperature at specific time intervals based on real sensor behavior, and fills in missing data during sensor failures. Tests show strong correlations between estimated and actual temperatures, allowing uninterrupted operation. This solution offers a flexible, cost-effective alternative to traditional redundancy, ensuring system reliability during sensor failures. Future research will explore alternative predictive models and conduct real-world testing to validate the system's resilience under complex conditions. © 2024 IEEE.

关键词： Temperature measurement

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Retrieving Masked Signal Through Tracking and Wavefront Shaping

Retrieving Masked Signal Through Tracking and Wavefront Shap...

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CLEO: Applications and Technology, A and T 2022

作者： Rumman, Nazifa Wang, Tianhong Jennings, Kaitlin Bassène, Pascal Buldt, Finn N'Gom, Moussa Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute TroyNY United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY United States

We present a novel approach that tracks and localizes hidden signal inside or behind scattering media. The method combines traditional feedback based wavefront shaping with a switch function that utilizes two differen...

ISBN: (纸本)9781957171050

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Optimal Control for Clutched-Elastic Robots: A Contact-Implicit Approach

Optimal Control for Clutched-Elastic Robots: A Contact-Impli...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Dennis Ossadnik Vasilije Rakčević Mehmet C. Yildirim Edmundo Pozo Fortunić Hugo T. M. Kussaba Abdalla Swikir Sami Haddadin Chair of Robotics and Systems Intelligence and the Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Germany Department of Electrical and Electronic Engineering Omar Al-Mukhtar University (OMU) Albaida Libya

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Intrinsically elastic robots surpass their rigid counterparts in a range of different characteristics. By temporarily storing potential energy and subsequently converting it to kinetic energy, elastic robots are capable of highly dynamic motions even with limited motor power. However, the time-dependency of this energy storage and release mechanism remains one of the major challenges in controlling elastic robots. A possible remedy is the introduction of locking elements (i.e. clutches and brakes) in the drive train. This gives rise to a new class of robots, so-called clutched-elastic robots (CER), with which it is possible to precisely control the energy-transfer timing. A prevalent challenge in the realm of CERs is the automatic discovery of clutch sequences. Due to complexity, many methods still rely on pre-defined modes. In this paper, we introduce a novel contact-implicit scheme designed to optimize both control input and clutch sequence simultaneously. A penalty in the objective function ensures the prevention of unnecessary clutch transitions. We empirically demonstrate the effectiveness of our proposed method on a double pendulum equipped with two of our newly proposed clutch-based Bi-Stiffness Actuators (BSA).

关键词： Potential energy Prevention and mitigation Optimal control Switches Motors Linear programming Timing

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Towards Instance Segmentation-Based Litter Collection with Multi-Rotor Aerial Vehicle

Towards Instance Segmentation-Based Litter Collection with M...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Filip Zoric Antonio Franchi Matko Orsag Zdenko Kovacic Chiara Gabellieri Laboratory for Robotics and Intelligent Control Systems (LARICS) at the Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Robotics and Mechatronics Group from the University of Twente Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a novel aerial robotics application of instance segmentation-based floating litter collection with a multi-rotor aerial vehicle (MRAV). In the scope of the paper, we present a review of the available datasets for litter detection and segmentation. The reviewed datasets are used to train a Mask-RCNN neural network for instance segmentation. The neural network is off-board deployed on an edge computing device and used for litter position estimation. Based on the estimated litter position, we plan a path based on a quadratic Bezier curve for the litter pickup. We compare different trajectory generation methods for the object pickup. The system is verified in a laboratory environment. Eventually, we present practical considerations and improvements necessary to enable autonomous litter collection with MRAV.

关键词： Instance segmentation Reviews Neural networks Laboratories Estimation Trajectory Aircraft

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Verifying Nonlinear Neural Feedback systems using Polyhedral Enclosures

arXiv

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arXiv 2025年

作者： Akinwande, Samuel I. Sidrane, Chelsea Kochenderfer, Mykel J. Barrett, Clark Department of Aeronautical and Astronautical Engineering Stanford University StanfordCA94305 United States Department of Computer Science Stanford University StanfordCA94305 United States Division of Robotics Perception and Learning Intelligent Systems Department School of Electrical Engineering & Computer Science KTH Royal Institute of Technology Stockholm Sweden

As dynamical systems equipped with neural network controllers (neural feedback systems) become increasingly prevalent, it is critical to develop methods to ensure their safe operation. Verifying safety requires extending control theoretic analysis methods to these systems. Although existing techniques can efficiently handle linear neural feedback systems, relatively few scalable methods address the nonlinear case. We propose a novel algorithm for forward reachability analysis of nonlinear neural feedback systems. The approach leverages the structure of the nonlinear transition functions of the systems to compute tight polyhedral enclosures (i.e., abstractions). These enclosures, combined with the neural controller, are then encoded as a mixed-integer linear program (MILP). Optimizing this MILP yields a sound over-approximation of the forward-reachable set. We evaluate our algorithm on representative benchmarks and demonstrate an order of magnitude improvement over the current state of the art. Copyright © 2025, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

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Human-as-advisor in the loop for autonomous lane-keeping

Human-as-advisor in the loop for autonomous lane-keeping

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American Control Conference (ACC)

作者： Rene Mai Sandipan Mishra Agung Julius Department of Mechanical Aerospace and Nuclear Engineering Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY

This paper presents a human-as-advisor architecture for shared human-machine autonomy in dynamic systems. In the human-as-advisor architecture, the human provides suggested control actions to the autonomous system; the system uses a model of the human controller to ascertain the system’s state as perceived by the human. The system combines this information with additional sensor measurements, yielding an improved state estimate. We apply this architecture to the problem of lane-centering an autonomous vehicle in the presence of conflicting lane markings that render the true lane center uncertain. We model conflicting lane markings with a multi-component Gaussian mixture model. The human-suggested course of action is interpreted as an additional sensor measurement, which a Kalman filter is designed to combine with a speedometer and camera for improving the state estimate. With human input from our human-as-advisor architecture, the vehicle centers itself in the lane; without human input, the vehicle does not center itself. We also demonstrate the human-as-advisor architecture is robust to additive output matrix uncertainty and non-linear perturbations in the human model used to interpret the human-suggested control actions.

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Intelligent Additive Manufacturing Architecture for Enhancing Uniformity of Surface Roughness and Mechanical Properties of Laser Powder Bed Fusion Components

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IEEE Transactions on Automation Science and engineering 2023年第4期20卷 2527-2538页

作者： Tran, Hong-Chuong Lo, Yu-Lung Yang, Haw-Ching Hsiao, Hung-Chang Cheng, Fan-Tien Kuo, Tsung-Han Southern Taiwan University of Science and Technology Department of Mechanical Engineering Tainan71005 Taiwan National Cheng Kung University Department of Mechanical Engineering Tainan70101 Taiwan National Kaohsiung First University of Science and Technology Department of Electrical Engineering Kaohsiung82445 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan Institute of Manufacturing Information and Systems National Cheng Kung University Tainan70101 Taiwan

In the Laser Powder Bed Fusion (L-PBF) process, 3D components with complex geometries are fabricated in a layer-by-layer fashion by using a controlled laser beam to selectively melt particular regions of the metal powder bed. However, due to the stochastic nature of the L-PBF process, the top surface roughness of each solidified layer tends to be different even when the optimal processing conditions for the different positions on the build plate are employed. As a result, the mechanical properties of the built components frequently vary from one component to the next. Accordingly, this study proposes an Intelligent Additive Manufacturing Architecture (IAMA) for controlling the surface roughness of each build layer through an appropriate adjustment of the laser re-melting parameters. The IAMA architecture comprises five modules, namely In-Situ Metrology (ISM), Ex-Situ Metrology (ESM), Automatic Virtual Metrology (AVM), Additive Manufacturing Simulation (AMS) and Intelligent Compensator (IC). The feasibility of the proposed architecture is demonstrated by comparing the top surface roughness of cubic and mechanical strengths of tensile test samples built using the proposed method with those built using a traditional L-PBF approach without surface roughness control. It is found that the samples fabricated using the IAMA approach have an average top surface roughness of 1.6μm and a standard deviation is 0.7μm. By contrast, the samples produced using the traditional L-PBF approach have an average surface roughness of 13.45μm and a standard deviation of 2.5μm. In addition, the specimens produced with the assistance of IAMA architecture have an average tensile strength of 1013 MPa with a standard deviation of 69.5 MPa, while those printed without surface roughness control have an average tensile strength of 903 MPa with a standard deviation of 101.4 MPa Note to Practitioners - As L-PBF produce part in a layer-by-layer manner, therefore, the roughness on the top surface of p

关键词： Surface roughness

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Object and Relation Centric Representations for Push Effect Prediction

SSRN

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SSRN 2023年

作者： Tekden, Ahmet E. Erdem, Aykut Erdem, Erkut Asfour, Tamim Ugur, Emre Computer Engineering Department Bogazici University Turkey Electrical Engineering Department Chalmers University of Technology Sweden Computer Engineering Department Koç University Turkey Computer Engineering Department Hacettepe University Turkey Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Germany

Pushing is an essential non-prehensile manipulation skill used for tasks ranging from pre-grasp manipulation to scene rearrangement, reasoning about object relations in the scene, and thus pushing actions have been widely studied in robotics. The effective use of pushing actions often requires an understanding of the dynamics of the manipulated objects and adaptation to the discrepancies between prediction and reality. For this reason, effect prediction and parameter estimation with pushing actions have been heavily investigated in the literature. However, current approaches are limited because they either model systems with a fixed number of objects or use image-based representations whose outputs are not very interpretable and quickly accumulate errors. In this paper, we propose a graph neural network based framework for effect prediction and parameter estimation of pushing actions by modeling object relations based on contacts or articulations. Our framework is validated both in real and simulated environments containing different shaped multi-part objects connected via different types of joints and objects with different masses, and it outperforms image-based representations on physics prediction. Our approach enables the robot to predict and adapt the effect of a pushing action as it observes the scene. It can also be used for tool manipulation with never-seen tools. Further, we demonstrate 6D effect prediction in the lever-up action in the context of robot-based hard-disk disassembly. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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A distributed algorithm with network-independent step-size and event-triggered mechanism for economic dispatch problem

A distributed algorithm with network-independent step-size a...

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作者： Chen, Baitong Yang, Jianhua Lu, Wei Pedrycz, Witold Sun, Changhai School of Control Science and Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology SARTaipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkey School of Electrical Engineering Dalian University of Technology Dalian China

The economic dispatch problem (EDP) poses a significant challenge in energy management for modern power systems, particularly as these systems undergo expansion. This growth escalates the demand for communication resources and increases the risk of communication failures. To address this challenge, we propose a distributed algorithm with network-independent step sizes and an event-triggered mechanism, which reduces communication requirements and enhances adaptability. Unlike traditional methods, our algorithm uses network-independent step sizes derived from each agent's local cost functions, thus eliminating the need for detailed network topology knowledge. The theoretical derivation identifies a range of step size values that depend solely on the objective function's strong convexity and the gradient's Lipschitz continuity. Furthermore, the proposed algorithm is shown to achieve a linear convergence rate, assuming the event triggering threshold criteria are met for linear convergence. Numerical experiments further validate the effectiveness and advantages of our proposed distributed algorithm by demonstrating its ability to maintain good convergence characteristics while reducing communication frequency. © 2024 John Wiley & Sons Ltd.

关键词： Cost functions

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