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检索条件"任意字段=Conference on Advanced Sensor and Control-System Interface"

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Multi-sensor Calibration system for Mobile Robots

Multi-sensor Calibration System for Mobile Robots

引用

conference on Vehicle control and Intelligence (CVCI)

作者： Wei Wu Chang Liu Wenhan Cao Chao Chen Hongbo Li Shengbo Eben Li School of Vehicle and Mobility Tsinghua University Beijing China Robot R&D Department Geekplus Corp. Beijing China Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China

Multi-sensor calibration is crucial for mobile robots, especially in logistics and warehouse environments. While calibration techniques exist for individual sensors, industry-level calibration of the multiple sensors on mobile robots covering the entire operational life cycle is rarely explored. To bridge the gap, we present a fast, accurate, and scalable calibration system supporting both manufacturing and operation phases for mobile robots with diverse sensors like odometers, IMUs, LiDARs, and cameras. Specifically, we propose an online yaw angle estimation approach for IMU by fusing odometer data as compensation. Additionally, we pioneer an approach to calibrate 2D LiDAR using surrounding objects’ reflectance strength as the calibration metric in the manufacturing phase calibration, and the iterative closest point method for refinements during operation phase calibration. Furthermore, we develop a least squares formulation to calibrate cameras’ intrinsic and extrinsic parameters, achieving rapid convergence. The system has been used by Geekplus across factories worldwide including Asia, Europe, America, and Oceania, successfully calibrating and deploying over 30,000 mobile robots.

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Application of the Computer system Component With Adjustment Elements For Processing sensor Signals 11

Application of the Computer System Component With Adjustment...

引用

11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and Applications (IDAACS)

作者： Ukhina, Hanna Sytnikov, Valerii Streltsov, Oleg Stupen, Pavel Kudria, Volodymyr Odessa Natl Polytech Univ Comp Syst Dept Odessa Ukraine

ISBN: (纸本)9781665426053

The paper deals with the computer systems frequency-dependent components using for processing sensor signals with the possibility of restructuring their characteristics. In the analysis course of second-order transfer functions, formulas were obtained that describe the numerator and denominator coefficients. The issues of stability express analysis and the transition process duration during restructuring are also considered. An example, the theoretical research application is given, which shows the restructuring efficiency on standard equations.

关键词： Internet of Things characteristics restructuring transfer function coefficients inclinometric sensor stability transient process duration

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Methodology for Hazard Identification and Mitigation Strategies Applied to an Overtaking Assistant ADAS

Methodology for Hazard Identification and Mitigation Strateg...

引用

IEEE Intelligent Transportation systems conference (ITSC)

作者： Capito, Linda Redmill, Keith A. Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

ISBN: (纸本)9781728191423

We propose a methodology for analyzing the hazards and potential mitigation of faults and failures in an advanced Driver Assistance system (ADAS) which is applicable to individual systems and subsystems of a larger automated vehicle implementation. To illustrate the methodology, we outline the structure of an notional overtaking assistant, considering that the system would not only need internal sensors such as global navigation satellite system (GNSS) receivers, map data, and other motion and localization sensors and external sensors such as radars, lidars, and vision systems but also access to cooperative positioning information through a wireless connected vehicular network in order to identify the location of oncoming traffic. Then, we perform the hazard analysis of this subsystem utilizing a combination of methods. For the vehicle level hazard analysis we use Hazard Operability Study (HAZOP) and the first step of system Theoretic Process Analysis (STPA), and for the overall safety analysis we use Failure Mode and Effects Analysis (FMEA) and the second step of STPA. An overtaking assistant for automated vehicles is considered a type of advanced Driver Assistant system (ADAS) that assists a partially or fully automated vehicle with an overtaking maneuver consisting of acceleration and steering control during a double lane change. Crash data indicates that although only 19% of the US population inhabits rural zones, 54% of the vehicular crashes happen on rural roads [1], with a high number of those events occurring during an overtaking maneuver on two-lane rural roads. While such an overtaking assistant would help to minimize these collision events, no commercial product is yet available due in part to the challenge of defining what constitutes safe navigation in these systems. The analysis performed on the system is presented and is proposed for use as a general methodology to analyze hazards in any ADAS system or subsystem. The summary of the analysis results pr

关键词： Wireless communication Wireless sensor networks Global navigation satellite system Roads Tools Hazards sensor systems

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Intelligent Lighting control system Using AI and IoT

Intelligent Lighting Control System Using AI and IoT

引用

Ubiquitous Computing and Intelligent Information systems (ICUIS), International conference on

作者： Mohamed Molham Saeed Rahaf Adel Al-Hamoud Adil Adam Computer Engineering ALZAHRAA UNIVERSITY Jarablus Aleppo Syria

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

As human society evolves, the demand for optimized and energy-efficient lighting solutions in buildings has intensified, driven by increasing energy consumption and the limitations of traditional systems in meeting the comfort and adaptability needs of modern users. This review study explores advanced intelligent lighting control systems suitable for indoor environments, highlighting the integration of Artificial Intelligence (AI) techniques with the Internet of Things (IoT) to enhance user comfort and reduce energy consumption. The systems discussed employ networks of connected motion and light sensors, interfaced through IoT platforms that enable real-time monitoring and adjustments based on room occupancy and natural lighting levels. Continuous data collection by these sensors facilitates dynamic illumination control, adapting to changing conditions throughout the day. Furthermore, intelligent system designs extend bulb life and minimize overall energy consumption by aligning lighting adjustments with user presence and daylight availability. Findings from existing studies and prototypes indicate that intelligent lighting systems not only enhance operational efficiency but also support sustainable energy practices. This review highlights the potential of intelligent lighting solutions for building resource-efficient and responsive building infrastructures, contributing to the broader goals of sustainability in modern architecture.

关键词： Energy consumption Reviews Lighting Lighting control sensor systems Real-time systems Energy efficiency Internet of Things Sustainable development Intelligent sensors

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CPITS 2022 - Proceedings of the Workshop on Cybersecurity Providing in Information and Telecommunication systems, co-located with International conference on Problems of Infocommunications. Science and Technology, PICST 2022

CPITS 2022 - Proceedings of the Workshop on Cybersecurity Pr...

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2022 Workshop on Cybersecurity Providing in Information and Telecommunication systems, CPITS 2022

The proceedings contain 19 papers. The topics discussed include: modeling CSIKE algorithm on non-cyclic Edwards curves;enterprise service bus construction in SOA architecture for SIEM implementation in critical information infrastructure;analysis and comparison of the NIST SP 800-53 and ISO/IEC 27001:2013;method of estimating the values of reliability indicators of objects with variable structure;study of the profitability of the enterprise based on the method of machine learning without a teacher;modifications of the correlation method of face detection in biometric identification systems;advanced communication model with the voice control and the increased security level;web-based management system for customer interaction in e-trade with adaptive interface;and on-time dependent linguistic graphs and solutions of postquantum multivariate cryptography.

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Eddy Current sensor as In-situ Assessment and Characterization of In-process Surface Defects in Wires/Rods Using Machine Learning Algorithms 1

Eddy Current Sensor as In-situ Assessment and Characterizati...

引用

1st IEEE IAS Global conference on Emerging Technologies, GlobConET 2022

作者： Dutta, Chandan Sagar, S. Palit Kumar, Alok Bhushan, Ravi Kadu, Satish Das, Tarun K. Csir - National Metallurgical Laboratory Nde and Magnetic Materials Group Advanced Materials and Processes Division Jamshedpur831007 India Tata Steel Ltd. Technology Group Long Products Tarapur Wire Mill India

ISBN: (数字)9781665443579

ISBN: (纸本)9781665443579

In-situ inspection of naturally grown in-process surface defects such as sliver, fin, chip-off, entrapment, abrasion, etc. of high-speed drawn steel wires/rods is indispensable nowadays for the wire drawing industries. The present communication aims at investigating a real-time assessment of such kinds of defects using machine learning (ML) algorithms. Emphasis has been laid on the development of assessment protocol for evaluation of figures of merits of their occurrences including the severity of defect prediction, minimum predictable resolution, computation efficiency, and range of defect classifications. A single tone encircling coil eddy current (EC) sensor along with an advanced signal processing toolkit is implemented to get the unique EC signal patterns that correspond to various kinds of defects. A linear sampling approach has been adopted using an automated motorized linear scanning system wherein the EC encircling coil scans the parts (wires/rods) axially and the EC signals corresponding to each kind of defect are logged into the PC. A set of algorithms based on support vector machine (SVM) has been trained against various defects which have been implemented for the classification of those in-process surface defects of the wires/rods obtained from plants. Various kinds of SVM Kernel functions have been trained using the experimental EC data. Amongst them, SVM with fine Gaussian Kernel functions is more robust in terms of prediction accuracy (~100%) and speed (~ 4500 observations per second). Moreover, the proposed SVM model is immune to noisy signals with SNR above 30 dB. From the perspective of the application, these findings indicate the importance of achieving higher efficiency combined with reliable quality control of the final products. © 2022 IEEE.

关键词： Neural networks

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Integrating Surface Electromyography with Assistive Robots for Elderly Care: A Novel Human-Robot interface for Grasping Tasks

Integrating Surface Electromyography with Assistive Robots f...

引用

International conference on advanced Cloud and Big Data (CBD)

作者： Qingyun Zhu Raviteja Tirumalapudi Junpei Zhong Yonghua Liu Mingjun Dai School of Automation Guangdong University of Technology Guangzhou China Aviation Services Research Centre The Hong Kong Polytechnic University Hong Kong China Faculty of Science and Technology University of Wollongong (College Hong Kong) Hong Kong College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798331511074

ISBN: (纸本)9798331511081

This paper presents a novel human-robot interface (HRI) for elderly care, integrating Surface Electromyography (sEMG) signals with an assistive robot to enhance grasping tasks. We introduce innovations in sEMG signal processing and classification methods optimized for older adults, along with efficient mapping of sEMG signals into precise control commands for assistive robots. Using a custom-designed armband device, we collected a unique dataset of four essential grasping gestures from older adults. Our machine learning-based classification algorithm demonstrates improved accuracy in gesture recognition for elderly users compared to existing methods. Experiments conducted with elderly participants showed shorter training times and higher success rates for grasping-related tasks compared to conventional interfaces. This research not only enhances the flexibility of robotic systems for elderly care but also provides a foundation for personalized assistance in daily activities. Our findings suggest that this sEMG-based robotic control system could improve the independence and quality of life for older adults. The paper concludes by discussing the advantages of our approach in the context of elderly care and outlines future directions for sEMG-based assistive robotics in gerontechnology.

关键词： Training Technological innovation Human-robot interaction Grasping Signal processing Assistive robots Electromyography Older adults Surface treatment Robots

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Camera-Radar-Based Adaptive Cross Attention Fusion for Multimodal Object Detection

Camera-Radar-Based Adaptive Cross Attention Fusion for Multi...

引用

International Automatic control conference

作者： Sin-Ye Jhong Wei-Jie Chang Hui-Che Hsu Shih-Hsuan Lin Shih-Che Chien Kai-Lung Hua Yung-Yao Chen

ISBN: (数字)9798350354904

ISBN: (纸本)9798350354911

advanced driver assistance systems (ADAS) necessitate the integration of data from multiple sensors for accurate environmental perception and object detection. However, fusing information from diverse sensors like cameras and radar presents substantial challenges due to inherent differences in data formats and the need for sophisticated fusion strategies. This paper introduces an Adaptive Cross Attention Fusion Module (ACAFM) tailored for the effective fusion of image and millimeter-wave radar data. By leveraging both channel and spatial attention mechanisms, our approach dynamically adjusts feature weighting during the fusion process, significantly improving detection accuracy and system stability. Evaluations on public datasets demonstrate that our method outperforms existing camera-radar fusion techniques, highlighting its robustness in complex and varied scenarios.

关键词： Accuracy Attention mechanisms Object detection Radar imaging Millimeter wave radar Feature extraction Stability analysis sensor systems sensors Autonomous vehicles

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A Logical Appliance of Deep Learning Methodology for an Intelligent Parking system for Smart Cities Using Internet of Things Association

A Logical Appliance of Deep Learning Methodology for an Inte...

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Electronics and Sustainable Communication systems (ICESC), 2020 International conference on

作者： G. Ramkumar Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

In this work, a novel Intelligent Parking system (IPS) for Smart Cities to improve large-scale urban parking management using Internet of Things (IoT) and Deep Learning techniques is proposed. The system is based on several sensors, cameras, and RFID readers that come together to provide an accurate real-time measurement of the occupation of parking spaces. Using the ImageNet database and utilizing a three-layered deep neural network with Convolutional Neural Networks (CNNs) for image processing, and Recurrent Neural Networks (RNNs) for predictive analytics, it delivers an accuracy rate of 95%, consuming only 300 milliseconds to the completion. The data is sent to a single cloud server using NodeMCU modules that update and back up the data regularly. A mobile application serves as the interface to the system for users who can check available spaces from anywhere, book space and pay for parking. The integration advanced AI methods not only optimizes the use of parking space and minimizes traffic congestion, but also helps to building smart urban environments sustainably. Future possibilities such as deeper integration with controlled vehicles, greater interoperability with other smart city components as well as dynamic pricing and customized user experiences have the capability to take urban mobility to the next level.

关键词： Deep learning Recurrent neural networks Accuracy Smart cities Aerospace electronics sensor systems Internet of Things Servers Vehicle dynamics Traffic congestion

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Industrial Augmented Reality: Connecting Machine-, NC- and sensor-Data to an AR Maintenance Support system

Industrial Augmented Reality: Connecting Machine-, NC- and S...

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28th IEEE conference on Virtual Reality and 3D User interfaces (IEEE VR)

作者： Lorenz, Mario Shandilya, Shamik Knopp, Sebastian Klimant, Philipp Tech Univ Chemnitz Inst Machine Tools & Prod Proc Chemnitz Germany Univ Hosp Leipzig Dept Orthoped Trauma & Plast Surg Leipzig Germany Med Univ Graz Dept Macroscop & Clin Anat Graz Austria

ISBN: (纸本)9781665440578

Access to machine data, e.g. axis positions inside an AR maintenance application can potentially increase the usefulness of AR in maintenance. Technicians walking to the machine control for looking up information would be avoided. However, the machine control interface and data are machine manufacturer depended, making it necessary to customize the interface between the machine control and the AR maintenance application. Here, we present a solution integrating machine control access from three different machines using a middleware box. A qualitative assessment with technicians confirms the usefulness direct machine data access from an AR maintenance application.

关键词： Augmented Reality Machine control Maintenance

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