scholarly journals LiDAR-Based Non-Cooperative Tumbling Spacecraft Pose Tracking by Fusing Depth Maps and Point Clouds

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3432 ◽  
Author(s):  
Gaopeng Zhao ◽  
Sixiong Xu ◽  
Yuming Bo
Keyword(s):  
Real Time ◽  
Point Cloud ◽  
High Speed ◽  
Grid Point ◽  
Point Clouds ◽  
Sensor Data ◽  
The Real ◽  
Pose Tracking ◽  
Depth Maps ◽  
Relative Pose

How to determine the relative pose between the chaser spacecraft and the high-speed tumbling target spacecraft at close range, which is an essential step in space proximity missions, is very challenging. This paper proposes a LiDAR-based pose tracking method by fusing depth maps and point clouds. The key point is to estimate the roll angle variation in adjacent sensor data by using the line detection and matching in depth maps. The simplification of adaptive voxelized grid point cloud based on the real-time relative position is adapted in order to satisfy the real-time requirement in the approaching process. In addition, the Iterative Closest Point algorithm is used to align the simplified sparse point cloud with the known target model point cloud in order to obtain the relative pose. Numerical experiments, which simulate the typical tumbling motion of the target and the approaching process, are performed to demonstrate the method. The experimental results show that the method has capability of estimating the real-time 6-DOF relative pose and dealing with large pose variations.

scholarly journals Real-Time Geometric Parameter Measurement of High-Speed Railway Fastener Based on Point Cloud from Structured Light Sensors

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3675 ◽  
Author(s):  
Hao Cui ◽  
Qingwu Hu ◽  
Qingzhou Mao
Keyword(s):  
Real Time ◽  
Geometric Parameter ◽  
Point Cloud ◽  
High Speed ◽  
Region Growing ◽  
Point Clouds ◽  
Parameter Measurement ◽  
High Speed Railway ◽  
Rail Track ◽  
Accuracy And Repeatability

With the increase in the number of service years for high-speed railways, the foundation of the rail track suffers from settlement, which causes rail track irregularity. To adjust the position of the track and meet track regularity demands, several components of the fastening system will be replaced by different sized components. It is important to measure the exact geometric parameters for the components of a fastening system before adjusting the track. Currently, the measurement process is conducted manually, which is laborious and error-prone. In this paper, a real-time geometric parameter measurement system for high-speed railway fastener based on 2-D laser profilers is presented. Dense and precise 3-D point clouds of high-speed railway fasteners are obtained from the system. A fastener extraction method is presented to extract fastener point cloud and a region-growing algorithm is used to locate key components of the fastener. Then, the geometric parameter of the fastener is worked out. An experiment was conducted on a high-speed railway near Wuhan, China to verify the accuracy and repeatability of the system. The maximum root-mean-square-error between the manual measurement and the system measurement is 0.3 mm, which demonstrates adequate accuracy. This system can replace manual measurements and greatly improve the efficiency of geometric parameter measurements for fasteners.

Application of the Real-Time EtherCAT Technology in Wind Power Control System

2012 ◽  
Vol 580 ◽  
pp. 155-159
Author(s):  
Xiang Ming Wang ◽  
Jin Chao Wang ◽  
Dong Hua Sun
Keyword(s):  
Control System ◽  
Real Time ◽  
Wind Power ◽  
High Speed ◽  
Communication Protocol ◽  
Data Communication ◽  
Data Acquisition System ◽  
Slave System ◽  
The Real ◽  
Wind Power System

In this paper, the real-time EtherCAT technology is introduced in detail, which including operating principle, communication protocol and the superiority performance of EtherCAT i.e. synchronicity, simultaneousness and high speed. To show how to design a slave system that considering the characteristics of application, the method of developing systems based no EtherCAT technology are proposed. Finally, a data acquisition system based on EtherCAT technology is designed. Application of EtherCAT technology can improve the real-time characteristics of data communication in wind power system.

Real-Time 3D object detection using improved convolutional neural network based on image-driven point cloud

2021 ◽  
Vol 14 ◽  
Author(s):  
Zhiyong Gao ◽  
Jianhong Xiang
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Convolutional Neural Network ◽  
Real Time ◽  
Point Cloud ◽  
Point Clouds ◽  
3D Point Cloud ◽  
3D Object ◽  
3D Object Detection ◽  
Instance Segmentation

Background: While detecting the object directly from the 3D point cloud, the natural 3D patterns and invariance of 3D data are often obscure. Objective: In this work, we aimed at studying the 3D object detection from discrete, disordered and sparse 3D point clouds. Methods: The CNN is composed of the frustum sequence module, 3D instance segmentation module S-NET, 3D point cloud transformation module T-NET, and 3D boundary box estimation module E-NET. The search space of the object is determined by the frustum sequence module. The instance segmentation of the point cloud is performed by the 3D instance segmentation module. The 3D coordinates of the object are confirmed by the transformation module and the 3D bounding box estimation module. Results: Evaluated on KITTI benchmark dataset, our method outperforms the state of the art by remarkable margins while having real-time capability. Conclusion: We achieve real-time 3D object detection by proposing an improved convolutional neural network (CNN) based on image-driven point clouds.

Disease Surveillance System for Big Climate Data Processing and Dengue Transmission

2017 ◽  
Vol 8 (2) ◽  
pp. 88-105 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Sensor Data ◽  
Climate Data ◽  
The Real ◽  
Disease Surveillance System

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.

scholarly journals AdaGUM: An Adaptive Graph Updating Model-Based Anomaly Detection Method for Edge Computing Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Yu ◽  
Chun Shan ◽  
Jilong Bian ◽  
Xianfei Yang ◽  
Ying Chen ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Anomaly Detection ◽  
Real Time ◽  
Detection Method ◽  
Edge Computing ◽  
Sensor Data ◽  
Computing Environment ◽  
The Real ◽  
Edge Node ◽  
Model Based

With the rapid development of Internet of Things (IoT), massive sensor data are being generated by the sensors deployed everywhere at an unprecedented rate. As the number of Internet of Things devices is estimated to grow to 25 billion by 2021, when facing the explicit or implicit anomalies in the real-time sensor data collected from Internet of Things devices, it is necessary to develop an effective and efficient anomaly detection method for IoT devices. Recent advances in the edge computing have significant impacts on the solution of anomaly detection in IoT. In this study, an adaptive graph updating model is first presented, based on which a novel anomaly detection method for edge computing environment is then proposed. At the cloud center, the unknown patterns are classified by a deep leaning model, based on the classification results, the feature graphs are updated periodically, and the classification results are constantly transmitted to each edge node where a cache is employed to keep the newly emerging anomalies or normal patterns temporarily until the edge node receives a newly updated feature graph. Finally, a series of comparison experiments are conducted to demonstrate the effectiveness of the proposed anomaly detection method for edge computing. And the results show that the proposed method can detect the anomalies in the real-time sensor data efficiently and accurately. More than that, the proposed method performs well when there exist newly emerging patterns, no matter they are anomalous or normal.

scholarly journals Geometric Modelling of Octagonal Lamp Poles

2014 ◽  
Vol XL-5 ◽  
pp. 145-150 ◽  
Author(s):  
T. O. Chan ◽  
D. D. Lichti
Keyword(s):  
Point Cloud ◽  
Geometric Model ◽  
Real Data ◽  
Point Clouds ◽  
Circular Cone ◽  
Basic Point ◽  
The Real ◽  
Cone Model ◽  
Proposed Model ◽  
Pole Point

Lamp poles are one of the most abundant highway and community components in modern cities. Their supporting parts are primarily tapered octagonal cones specifically designed for wind resistance. The geometry and the positions of the lamp poles are important information for various applications. For example, they are important to monitoring deformation of aged lamp poles, maintaining an efficient highway GIS system, and also facilitating possible feature-based calibration of mobile LiDAR systems. In this paper, we present a novel geometric model for octagonal lamp poles. The model consists of seven parameters in which a rotation about the z-axis is included, and points are constrained by the trigonometric property of 2D octagons after applying the rotations. For the geometric fitting of the lamp pole point cloud captured by a terrestrial LiDAR, accurate initial parameter values are essential. They can be estimated by first fitting the points to a circular cone model and this is followed by some basic point cloud processing techniques. The model was verified by fitting both simulated and real data. The real data includes several lamp pole point clouds captured by: (1) Faro Focus 3D and (2) Velodyne HDL-32E. The fitting results using the proposed model are promising, and up to 2.9 mm improvement in fitting accuracy was realized for the real lamp pole point clouds compared to using the conventional circular cone model. The overall result suggests that the proposed model is appropriate and rigorous.

scholarly journals Development of six-degree of freedom strapdown terrestrial INS algorithm

2005 ◽  
Vol 2 (1) ◽  
pp. 155-165
Author(s):  
Baghdad Science Journal
Keyword(s):  
Real Time ◽  
High Speed ◽  
Degree Of Freedom ◽  
The Real ◽  
Six Degree Of Freedom

Many of accurate inertial guided missilc systems need to use more complex mathematical calculations and require a high speed processing to ensure the real-time opreation. This will give rise to the need of developing an effcint

A Real-Time Hard X-Ray Tomographic System Designed for HL-2A Fast Electron Bremsstrahlung Radiation

2020 ◽  
Author(s):  
Chen Yuan ◽  
Jun Wu
Keyword(s):  
Real Time ◽  
Fast Electron ◽  
High Speed ◽  
Lower Hybrid ◽  
Processing Unit ◽  
Bremsstrahlung Radiation ◽  
X Ray ◽  
The Real ◽  
Electron Bremsstrahlung ◽  
Plasma State

Abstract A real-time hard X-ray (HXR) tomographic system is designed for HL-2A tokamak, which is dedicated to the real-time tomography of fast electron bremsstrahlung radiation during the lower hybrid (LH) driven mode within the energy range of 20keV to 200keV. This system has realized the investigation of HXR energy from 12 different chords on the equatorial plane of the reaction region. The spatial and temporal resolutions of the system are 2cm and 10ms, separately. HXR detection is accomplished by a self-designed detector array, with a structure of 12 arc arranged cadmium telluride (CdTe) semiconductors and their corresponding collimators. The real-time HXR acquisition and processing is achieved by the main electronic system, which is comprised of a high speed analog-to-digital module and a high performance signal processing unit. Due to high HXR flux and the real-time demand in measurement, the HXR tomography is accomplished by several customized digital processing algorithms based on FPGA logic resources, such as the digital real-time spectrum measurement, the trapezoidal shaper, the pile up filter, and the baseline restorer, etc. This system has been proved to be qualified as a dependable platform of fast electron bremsstrahlung radiation research during LH mode on HL-2A, which provides indispensable parameters for plasma state during fusion reaction.

scholarly journals PLIN: A Network for Pseudo-LiDAR Point Cloud Interpolation

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1573 ◽  
Author(s):  
Haojie Liu ◽  
Kang Liao ◽  
Chunyu Lin ◽  
Yao Zhao ◽  
Meiqin Liu
Keyword(s):  
Point Cloud ◽  
Spatial Information ◽  
Interpolation Method ◽  
Low Frequency ◽  
Point Clouds ◽  
Autonomous Driving ◽  
Sensor Data ◽  
Navigation Systems ◽  
Intermediate Point ◽  
Cascade Structure

LiDAR sensors can provide dependable 3D spatial information at a low frequency (around 10 Hz) and have been widely applied in the field of autonomous driving and unmanned aerial vehicle (UAV). However, the camera with a higher frequency (around 20 Hz) has to be decreased so as to match with LiDAR in a multi-sensor system. In this paper, we propose a novel Pseudo-LiDAR interpolation network (PLIN) to increase the frequency of LiDAR sensor data. PLIN can generate temporally and spatially high-quality point cloud sequences to match the high frequency of cameras. To achieve this goal, we design a coarse interpolation stage guided by consecutive sparse depth maps and motion relationship. We also propose a refined interpolation stage guided by the realistic scene. Using this coarse-to-fine cascade structure, our method can progressively perceive multi-modal information and generate accurate intermediate point clouds. To the best of our knowledge, this is the first deep framework for Pseudo-LiDAR point cloud interpolation, which shows appealing applications in navigation systems equipped with LiDAR and cameras. Experimental results demonstrate that PLIN achieves promising performance on the KITTI dataset, significantly outperforming the traditional interpolation method and the state-of-the-art video interpolation technique.

A Discussion about FBG Sensors Application of Crane SHM System

2013 ◽  
Vol 336-338 ◽  
pp. 185-191
Author(s):  
Xiao Peng Xie ◽  
Dong Hui Wang ◽  
Guo Jian Huang ◽  
Xin Hua Wang
Keyword(s):  
Finite Element ◽  
Real Time ◽  
Failure Modes ◽  
Safety Evaluation ◽  
Structural Condition ◽  
Sensor Data ◽  
Gantry Crane ◽  
The Real ◽  
Time Stress ◽  
Fbg Sensors

The arrangement positions and the quantities are different for different types of cranes. In order to make suitable decision, much investigate and survey was done at preliminary stage, and we know that the flange connected gate legs and turntables, the connections between load-bearing beam and rotary column under the engine room and the connections between jib and turntable are easy to lose efficient, and their mainly failure modes are cracks. By the method of finite element, 32 sensors (including 21 welding strain FBG sensors and 11 temperature FBG sensors) were used after doing much investigate and survey and finite element modeling analysis, which are arranged in different places of a gantry crane of MQ2533, for real-time structure health monitoring. This method makes the sensor data obtained more realistically reflects the crane structural condition, which provides reliable data support for crane safety monitoring and safety evaluation. Then a software platform is developed to monitor the real-time stress. If the real-time stress exceeds the allowable stress, it issues an alarm signal to the operator.

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