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arXiv 2024年

作者： Verhagen, Joris Lindemann, Lars Tumova, Jana The Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden The Thomas Lord Department of Computer Science University of Southern California Los AngelesCA United States

This work addresses maximally robust control synthesis under unknown disturbances. We consider a general nonlinear system, subject to a Signal Temporal Logic (STL) specification, and wish to jointly synthesize the maximal possible disturbance bounds and the corresponding controllers that ensure the STL specification is satisfied under these bounds. Many works have considered STL satisfaction under given bounded disturbances. Yet, to the authors' best knowledge, this is the first work that aims to maximize the permissible disturbance set and find the corresponding controllers that ensure satisfying the STL specification with maximum disturbance robustness. We extend the notion of disturbance-robust semantics for STL, which is a property of a specification, dynamical system, and controller, and provide an algorithm to get the maximal disturbance robust controllers satisfying an STL specification using Hamilton-Jacobi reachability. We show its soundness and provide a simulation example with an Autonomous Underwater Vehicle (AUV). Copyright © 2024, The Authors. All rights reserved.

关键词： Controllers

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Secured Framework for Vehicle Management Using Blockchain

Secured Framework for Vehicle Management Using Blockchain

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： Poonguzhali N N. Amarabalan School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India Department of Electrical and Electronics Engineering Manakula Vinayagar Institute of Technology Puducherry India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

For many years, there were many different ways to arrange a vehicle's information using just the license plate. The number on a vehicle's license plate is the primary symbol used to identify it. The industries used to reciprocate the number plates in order to further uphold their basic standards. Anonymization through encryption is the preferred privacy setting for a license plate. We will have access to all the services required for faultless data maintenance through the Vehicle Management system. The entire system depends on the data, which is technologically encrypted and decrypted. However, data stored on a chip will be more secure than image recognition. It reduces the likelihood of mistakes and misunderstandings of the required information. Vehicle-related data is stored in a decentralized system. The suggested system either retrieves data from the smart number plate or uses an image processing technique to determine the license plate number through edge detection. The required data can be seen with this number. In order to ensure security, these data are encrypted using the SHA-256 algorithm and stored in a decentralized system using the Hyperledger Sawtooth framework, which also employs the PoET and BFT algorithms.

关键词： Industries Privacy Image edge detection Symbols Maintenance Information filtering Encryption License plate recognition Standards Information integrity

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KinGloves: Rapid Prototyping of Usability Enhanced Sensing Gloves for Parkinson's Disease

KinGloves: Rapid Prototyping of Usability Enhanced Sensing G...

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2024 International Conference on the Challenges, Opportunities, Innovations and Applications in Electronic Textiles, E-Textiles 2024

作者： Ravichandran, Vignesh Chomal, Shubham Arruda, Rachel Al Rumon, Md Abdullah Dupre, Anne-Marie Fapohunda, Kofoworola Tandon, Puneet Owens, Jim Macht, Gretchen Kosiba-Quiterio, Carolyn Solanki, Dhaval Mankodiya, Kunal University of Rhode Island Department of Electrical Computer and Biomedical Engineering KingstonRI United States Indian Institute of Information Technology Design and Manufacturing Department of Mechanical Industrial and Systems Engineering KingstonRI United States University of Rhode Island Department of Mechanical Industrial and Systems Engineering KingstonRI United States University of Rhode Island Department of Textiles Fashion Merchandising and Design KingstonRI United States University of Rhode Island Department of Physical Therapy KingstonRI United States Nautilus Defense PawtucketRI United States Rock Steady Boxing East GreenwichRI United States

ISBN: (纸本)9783000804298

Parkinson's Disease (PD) is a progressive neurological movement disorder causing motor (movement) impairments, leading to difficulty in performing activities of daily living such as eating, writing, cutting vegetables, buttoning a shirt, tying shoelaces, brushing teeth, etc. Although sensing clothes has gained popularity in monitoring disease progression in home settings, they pose usability challenges arising from movement/cognitive symptoms that hamper their adoption and adherence. In this study, we employ a user-centered design process with an aim to improve the wearability of gloves through a multi-phase study involving 23 people with PD (PwPD). The goal was to design gloves with suitable wrist closure and finger insertion mechanisms to enable independent upper-body movement assessments. The first phase conducted with 4 PwPD helped identify preferred and undesired glove-wearing mechanics through 12 daily living tasks. Next, a rapid prototyping process for textiles, using a laser cutter, produced three design concepts for evaluation by 9 PwPD. The best-performing prototype design was chosen for capacitive sensing thread integration and design revision. The capacitive sensing threads play a crucial role in accurately measuring finger flexion and extension, providing high-resolution data on hand movements that are critical for assessing finger movements associated with Parkinson's Disease symptoms. After incorporating participant feedback, the improved design had an average reduction of 23% in time to wear and 250% in time to take off when tested with 18 PwPD. In particular, features such as a view window for fingers and use of zippers had been reported by participants to improve glove usability. © 2024 Fraunhofer IZM.

关键词： User centered design

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment

A Modified Dempster Shafer Approach to Classification in Sur...

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Iranian Conference on electrical engineering (ICEE)

作者： Arash Iranfar Mohammad Soleymannejad Behzad Moshiri Hamid D. Taghirad School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.

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Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

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computer systems Science & engineering 2023年第8期46卷 2319-2335页

作者： Saud Yonbawi Sultan Alahmari B.R.S.S.Raju Chukka Hari Govinda Rao Mohamad Khairi Ishak Hend Khalid Alkahtani JoséVarela-Aldás Samih M.Mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Aditya Engineering College Affiliated to JNTUK(Kakinada) SurampalemIndia Department of MBA Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia SISAu Research Group Universidad Tecnológica IndoaméricaAmbato180103Ecuador Faculty of Computers and Information South Valley UniversityQena83523Egypt

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual *** the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart *** irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation *** learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an *** this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent *** MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination ***,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not *** MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

关键词： Agriculture smart farming hyperparameter tuning artificial intelligence irrigation management sensors deep learning

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Fault Diagnostic Opportunities for Electromagnetic Coils of Active Magnetic Bearings using Physics-of-Failure Analysis 5

Fault Diagnostic Opportunities for Electromagnetic Coils of ...

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5th International Conference on System Reliability and Safety engineering, SRSE 2023

作者： Li, Ruiqi Wang, Kai Zeng, Peng Cao, Jiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Harbin Institute of Technology Department of Electrical Engineering China

ISBN: (纸本)9798350305944

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. They are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed. © 2023 IEEE.

关键词： Failure analysis

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Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames

Manipulation-Oriented Object Perception in Clutter through A...

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IEEE-RAS International Conference on Humanoid Robots

作者： Xiaotong Chen Kaizhi Zheng Zhen Zeng Cameron Kisailus Shreshtha Basu James Cooney Jana Pavlasek Odest Chadwicke Jenkins Department of Electrical Engineering and Computer Science Robotics Institute at the University of Michigan Ann Arbor MI USA

ISBN: (纸本)9798350309805

In order to enable robust operation in unstructured environments, robots should be able to generalize ma-nipulation actions to novel object instances. For example, to pour and serve a drink, a robot should be able to recognize novel containers which afford the task. Most importantly, robots should be able to manipulate these novel containers to fulfill the task. To achieve this, we aim to provide robust and generalized perception of object affordances and their associated manipulation poses for reliable manipulation. In this work, we combine the notions of affordance and category-level pose, and introduce the Affordance Coordinate Frame (ACF). With ACF, we represent each object class in terms of individual affordance parts and the compatibility between them, where each part is associated with a part category-level pose for robot manipulation. In our experiments, we demonstrate that ACF outperforms state-of-the-art methods for object detection, as well as category-level pose estimation for object parts. We further demonstrate the applicability of ACF to robot manipulation tasks through experiments in both simulation and real world environment.

关键词： Deep learning Affordances Robot kinematics Pose estimation Humanoid robots Object detection Containers

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Robust Stochastic Shortest-Path Planning via Risk-Sensitive Incremental Sampling

arXiv

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arXiv 2024年

作者： Enwerem, Clinton Noorani, Erfaun Baras, John S. Sadler, Brian M. The Department of Electrical & Computer Engineering The Institute for Systems Research University of Maryland College ParkMD United States The University of Texas AustinTX United States

With the pervasiveness of Stochastic Shortest-Path (SSP) problems in high-risk industries, such as last-mile autonomous delivery and supply chain management, robust planning algorithms are crucial for ensuring successful task completion while mitigating hazardous outcomes. Mainstream chance-constrained incremental sampling techniques for solving SSP problems tend to be overly conservative and typically do not consider the likelihood of undesirable tail events. We propose an alternative risk-aware approach inspired by the asymptotically-optimal Rapidly-Exploring Random Trees (RRT*) planning algorithm, which selects nodes along path segments with minimal Conditional Value-at-Risk (CVaR). Our motivation rests on the step-wise coherence of the CVaR risk measure and the optimal substructure of the SSP problem. Thus, optimizing with respect to the CVaR at each sampling iteration necessarily leads to an optimal path in the limit of the sample size. We validate our approach via numerical path planning experiments in a two-dimensional grid world with obstacles and stochastic path-segment lengths. Our simulation results show that incorporating risk into the tree growth process yields paths with lengths that are significantly less sensitive to variations in the noise parameter, or equivalently, paths that are more robust to environmental uncertainty. Algorithmic analyses reveal similar query time and memory space complexity to the baseline RRT* procedure, with only a marginal increase in processing time. This increase is offset by significantly lower noise sensitivity and reduced planner failure rates. © 2024, CC BY.

关键词： Stochastic systems

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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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IEEE Conference on Decision and Control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory HUNREN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

关键词： Technological innovation Sensitivity Frequency-domain analysis Stability criteria Prototypes Throughput Frequency response Motion control Optimization MIMO communication

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Robust Output Feedback MPC with Reduced Conservatism under Ellipsoidal Uncertainty

Robust Output Feedback MPC with Reduced Conservatism under E...

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IEEE Conference on Decision and Control

作者： Tianchen Ji Junyi Geng Katherine Driggs-Campbell Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Robotics Institute Carnegie Mellon University

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

Robust design of autonomous systems under uncertainty is an important yet challenging problem. This work proposes a robust controller that consists of a state estimator and a tube based predictive control law. The class of linear systems under ellipsoidal uncertainty is considered. In contrast to existing approaches based on polytopic sets, the constraint tightening is directly computed from the ellipsoidal sets of disturbances without over-approximation, thus leading to less conservative bounds. Conditions to guarantee robust constraint satisfaction and robust stability are presented. Further, by avoiding the usage of Minkowski sum in set computation, the proposed approach can also scale up to high-dimensional systems. The results are illustrated by examples.

关键词： Linear systems Uncertainty Robust stability Economic indicators Computational modeling Predictive models Electron tubes

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