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IEEE International conference on Robotics and Automation (ICRA)

作者： Huang, Jui-Te Xu, Ruoyang Hinduja, Akshay Kaess, Michael Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9798350384581;9798350384574

State estimation is a crucial component for the successful implementation of robotic systems, relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios, the performance of these sensors is degraded by challenging environments, e.g. adverse weather conditions and low-light scenarios. The emerging 4D imaging radar technology is capable of providing robust perception in adverse conditions. Despite its potential, challenges remain for indoor settings where noisy radar data does not present clear geometric features. Moreover, disparities in radar data resolution and field of view (FOV) can lead to inaccurate measurements. While prior research has explored radar-inertial odometry based on Doppler velocity information, challenges remain for the estimation of 3D motion because of the discrepancy in the FOV and resolution of the radar sensor. In this paper, we address Doppler velocity measurement uncertainties. We present a method to optimize body frame velocity while managing Doppler velocity uncertainty. Based on our observations, we propose a dual imaging radar configuration to mitigate the challenge of discrepancy in radar data. To attain high-precision 3D state estimation, we introduce a strategy that seamlessly integrates radar data with a consumer-grade IMU sensor using fixed-lag smoothing optimization. Finally, we evaluate our approach using real-world 3D motion data.

关键词： radar imaging

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Research on visualization technology of data Mining Based on RD-SOM (radar-Self-Organizing Map) Clustering Algorithm 3

Research on Visualization Technology of Data Mining Based on...

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3rd International conference on Cloud Computing, Big data Application and Software Engineering, CBASE 2024

作者： Ma, Bing Li, Dongsheng Liu, Xiaotan Mai, Yiyuan Qin, Shasha PLAA Infantry College PLAA Infantry College Shijiaozhuang Hebei China Hunan Changsha75841 China Hainan Hospital of Chinese PLA General Hospital Hainan Sanya China

ISBN: (纸本)9798331506582

With the continuous development of data storage, analysis, processing and other technologies, people are eager to visualize the mining process of complex data, and data mining visualization technology is gradually applied to all fields of society, which greatly improves the efficiency of data mining [1]. The author starts with data visualization technology, studies data preprocessing and algorithms, and proposes data mining visualization technology of RD-SOM clustering algorithm by analyzing the existing problems in the current SOM clustering algorithm, so as to improve the current algorithm and obtain higher data utilization rate. © 2024 IEEE.

关键词： data assimilation

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Laser-Powered Extensometer for Soil Displacement Monitoring 13

Laser-Powered Extensometer for Soil Displacement Monitoring

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2024 International conference on radar Antenna Microwave Electronics and Telecommunications

作者： Nelfyenny, Nelfyenny Sebastian, Raditya Suryadi Bayuwati, Dwi Mulyanto, Imam Qomaruddin, Qomaruddin Widiyatmoko, Bambang Setiono, Andi Natl Res & Innovat Agcy Res Ctr Photon South Tangerang Indonesia Jakarta State Univ Dept Phys Jakarta Indonesia

ISBN: (纸本)9798350389937;9798350389920

The Earth's geological diversity exposes regions to various natural hazards, including earthquakes, landslides, and volcanic eruptions, with soil displacement posing significant risks to infrastructure stability and agricultural productivity. Previous landslide monitoring systems encountered challenges such as data transmission stability and the vulnerability of power supply systems. In response, a soil displacement monitoring system is proposed, integrating extensometer sensors with advanced fiber optic communication technology and a laser-based power system. Extensometer sensors, known for their precise soil displacement measurements, face difficulties in long-distance data transmission, addressed by fiber optic communication offering higher bandwidth and extended transmission distances. The laser-based power system enhances system reliability and efficiency through fiber optics, ensuring uninterrupted operation even in remote locations. System accessibility is further facilitated with a Python-based graphical user interface (GUI) for real-time data visualization. The system's performance is validated through comprehensive soil displacement simulations, supported by continuous monitoring using a rain simulator to observe potential displacements. This integrated approach, leveraging a robust laser-based power system and advanced communication technology, aims to enhance disaster management strategies in geologically active regions.

关键词： disaster management strategies extensometer fiber optic communication laser powering real-time data visualization soil displacement monitoring

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SLAM Algorithm Based on Heterogeneous sensor data Fusion 36

SLAM Algorithm Based on Heterogeneous Sensor Data Fusion

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36th Chinese Control and Decision conference (CCDC)

作者： Dou, Jianbin Xu, Chen Tang, Zhicheng Anhui Univ Sch Artificial Intelligence Hefei Peoples R China

ISBN: (纸本)9798350387780;9798350387797

With the rapid development of artificial intelligence technology, simultaneous localization and mapping (SLAM), as a key technology, has attracted widespread attention. However, laser-based SLAM technology suffers from significant drift issues. A heterogeneous sensor data fusion algorithm aimed at improving the performance of SLAM is proposed in this paper. First, data from laser radar and the Inertial Measurement Unit (IMU) is collected. Then, the Cartographer algorithm itself employs the Extended Kalman Filter (EKF) method to fuse the data from both sources, ultimately constructing a 2D SLAM framework for environmental mapping. Laser radar data and FAN data from three different experimental scenarios are collected, and the mentioned algorithm is utilized to fuse the data for map construction. The error between the constructed map and the real map is compared, demonstrating that the heterogeneous sensor data fusion-based SLAM algorithm in this paper outperforms single lidar Cartographer. It overcame the issue of rotational drift and exhibited promising application potential.

关键词： SLAM Cartographer EKF IMU LIDAR

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Measurement of pH Water Based on sensor, Arduino and Solar Cell in Laser Communication 13

Measurement of pH Water Based on Sensor, Arduino and Solar C...

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2024 International conference on radar Antenna Microwave Electronics and Telecommunications

作者： Assaidah Juri, Saifudin Ariani, Menik Saleh, Khairul Fitri, Yulia Handayani, Feriska Univ Sriwijaya Dept Phys Palembang Indonesia Univ Muhammadiyah Riau Dept Phys Pekanbaru Indonesia Univ Andalas Dept Phys Padang Indonesia

ISBN: (纸本)9798350389937;9798350389920

We connected pH sensor and solar cell into Arduino Board to control data transmission via red laser communication or popular known as visible light communication (VLC). The sensor was calibrated through pH water solution measurement compared with conventional pH Meter. This sensor collected and then modulated pH data in Arduino to be sent via laser beam. The beam is captured by solar cell which acts as a photodetector in receiver. The received data will be demodulated in Arduino to be displayed in serial monitor to observe the communication performance. As the result, the link distance of laser communication can reach 35 m using 1-PWM and 15 m using 2-PWM, in free-space environment. When the transmission channel was changed into water environment, the link distance will decrease severely. The prototype output of this work will be a future self-powered modem for water surface and underwater monitoring system.

关键词： pH laser Arduino solar cell VLC

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To Design and Implement a radar System using Arduino and Ultrasonic sensor 2

To Design and Implement a Radar System using Arduino and Ult...

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2nd International conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Rajeswari, Mummadi Lingappa, J. Basha, Mulla Gouse Deepa, Velagapuri Sravani, Vajrapu Srilatha, Kommidi Department of ECE Teegala Krishan Reddy Engineering College India Department of EEE Geethanjali College of Engineering and Technology India

ISBN: (纸本)9798350340235

radar technology has been a cornerstone of numerous applications, from aviation to meteorology, offering invaluable capabilities for object detection and tracking. Traditional radar systems, while powerful, often come with significant costs and complexities, limiting their accessibility in various fields. In response to these limitations, this research endeavors to design and implement a radar system using Arduino microcontrollers and ultrasonic sensors. This innovative approach leverages the flexibility and affordability of the Arduino platform and the distance measurement precision of ultrasonic sensors to create a radar-like system. The research encompasses the development of the hardware, data acquisition, signal processing, and real-time visualization, providing an accessible and cost-effective alternative for radar-based applications. The study explores the integration of Arduino technology and ultrasonic sensors into radar systems, with a focus on simplicity, affordability, and practicality. By bridging the gap between traditional radar systems and DIY electronics, this research aims to democratize radar technology and open doors for applications in robotics, smart cities, industrial automation, and education. The findings presented here offer new perspectives on radar system design and underscore the potential for radar innovation in emerging fields. © 2023 IEEE.

关键词： Arduino radar system Servomotor Ultrasonic sensor

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Micro-Doppler radar characterization of vehicle vibrations 28

Micro-Doppler radar characterization of vehicle vibrations

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conference on radar sensor technology XXVIII

作者： Simone, Benjamin D. Narayanan, Ram M. Watson, Daniel K. Reichard, Karl M. Gallagher, Kyle A. Penn State Univ Dept Elect Engn University Pk PA 16802 USA Penn State Univ Appl Res Lab University Pk PA 16802 USA DEVCOM Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9781510674158;9781510674141

Micro-Doppler radar is a cutting-edge technology that has revolutionized the field of radar sensing to enable the detection and characterization of complex targets by leveraging their micro-motion dynamics. This paper discusses the design and construction of a 10-GHz continuous wave (CW) micro-Doppler radar, an explanation of how the system operates and extracts data, as well as a discussion of the device's possible applications for characterizing external vibrations of vehicles under different scenarios. The objective is to highlight the potential of micro-Doppler radar for remotely recognizing vehicle transmission shifts and occupancy.

关键词： radar Micro-Doppler Vibrations Vehicle Spectrograms Raspberry Pi

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Multimodal Odometry Estimation With Automated sensor Selection 27

Multimodal Odometry Estimation With Automated Sensor Selecti...

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27th International conference on Information Fusion (FUSION)

作者： Michaelis, Martin Berthold, Philipp Luettel, Thorsten Maehlisch, Mirko Univ Bundeswehr Munich Inst Autonomous Syst Technol TAS Neubiberg Germany

ISBN: (纸本)9798350371420;9781737749769

For autonomous driving applications, knowledge of the ego position, orientation, and velocity is a necessary prerequisite for recognizing landmarks and moving targets. We use radar sensors for the determination of these quantities in a radar odometry system. radar odometry uses the advantage of a direct measurement of the radial speed using radar sensors. radar sensors are less susceptible to bad weather and lighting conditions than camera and lidar sensors. In addition, radar data is not susceptible to wheel slippage or blocked wheels compared with wheel speed measurements. However, radar data is still susceptible to clutter. In order to achieve a combination of good precision under optimal conditions and good precision under adverse weather conditions, we fuse measurements from radar sensors, wheel speed sensors and the gyrometer. We do not simply combine these measurements according to assumed covariances. Instead, we check the plausibility of the measurements based on their likelihood. Subsequently, we weight the results of the sensor combinations accordingly. The decision about sensor weighting is carried out in a principled, probabilistic manner and adaptively with regard to environmental influences. We validate our approach using real data. Our approach is more precise under adverse conditions than using wheel speed sensors and gyrometers alone. On the other hand, it is more precise under good conditions than using only radar measurements.

关键词： radar measurement

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Enhancing Object Recognition with Multi-View radar data using Convolutional Neural Network 16

Enhancing Object Recognition with Multi-View Radar Data usin...

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16th International conference on Microwave and Millimeter Wave technology (ICMMT)

作者： Wang, Pai Zhuge, Xiaodong Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China

ISBN: (纸本)9798350389968

In the realm of autonomous driving, millimeter-wave radar is widely acknowledged as a potent and cost-effective solution for object recognition. In this paper, we propose an improved RAMP-CNN network for radar object recognition by optimizing high-dimensional data projection branches, eliminating the feature fusion and introducing a coherence loss function. Our experiments, conducted on a self-collected multi-person radar dataset, illustrate that the enhanced network achieved approximately 3% improvement, attaining an average precision (AP) of 84.7% and an average recall (AR) of 88.6% in object detection performances.

关键词： Convolutional neural networks

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LiV-GS: LiDAR-Vision Integration for 3D Gaussian Splatting SLAM in Outdoor Environments

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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第1期10卷 421-428页

作者： Xiao, Renxiang Liu, Wei Chen, Yushuai Hu, Liang Harbin Inst Technol Sch Mech Engn & Automat Dept Automat Shenzhen 150001 Peoples R China

We present LiV-GS, a LiDAR-visual SLAM system in outdoor environments that leverages 3D Gaussian as a differentiable spatial representation. Notably, LiV-GS is the first method that directly aligns discrete and sparse LiDAR data with continuous differentiable Gaussian maps in large-scale outdoor scenes, overcoming the limitation of fixed resolution in traditional LiDAR mapping. The system aligns point clouds with Gaussian maps using shared covariance attributes for front-end tracking and integrates the normal orientation into the loss function to refines the Gaussian map. To reliably and stably update Gaussians outside the LiDAR field of view, we introduce a novel conditional Gaussian constraint that aligns these Gaussians closely with the nearest reliable ones. The targeted adjustment enables LiV-GS to achieve fast and accurate mapping with novel view synthesis at a rate of 7.98 FPS. Extensive comparative experiments demonstrate LiV-GS's superior performance in SLAM, image rendering and mapping. The successful cross-modal radar-LiDAR localization highlights the potential of LiV-GS for applications in cross-modal semantic positioning and object segmentation with Gaussian maps.

关键词： Laser radar Point cloud compression Simultaneous localization and mapping Three-dimensional displays Image reconstruction Cameras Rendering (computer graphics) visualization Image color analysis sensors Mapping SLAM range sensing multi-sensor fusion 3D Gaussian splatting

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