scholarly journals Three-Dimensional Visualization System with Spatial Information for Navigation of Tele-Operated Robots

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 746 ◽  
Author(s):  
Seung-Hun Kim ◽  
Chansung Jung ◽  
Jaeheung Park
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Effective Control ◽  
Visualization System ◽  
Level Information ◽  
Surrounding Space ◽  
The Right ◽  
High Level

This study describes a three-dimensional visualization system with spatial information for the effective control of a tele-operated robot. The environmental visualization system for operating the robot is very important. The tele-operated robot performs tasks in a disaster area that is not accessible to humans. The visualization system should perform in real-time to cope with rapidly changing situations. The visualization system should also provide accurate and high-level information so that the tele-operator can make the right decisions. The proposed system consists of four fisheye cameras and a 360° laser scanner. When the robot moves to the unknown space, a spatial model is created using the spatial information data of the laser scanner, and a single-stitched image is created using four images from cameras and mapped in real-time. The visualized image contains the surrounding spatial information; hence, the tele-operator can not only grasp the surrounding space easily, but also knows the relative position of the robot in space. In addition, it provides various angles of view without moving the robot or sensor, thereby coping with various situations. The experimental results show that the proposed method has a more natural appearance than the conventional methods.

scholarly journals On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements

2018 ◽  
Vol 8 (2) ◽  
pp. 20170039 ◽  
Author(s):  
Zhan Li ◽  
Michael Schaefer ◽  
Alan Strahler ◽  
Crystal Schaaf ◽  
David Jupp
Keyword(s):  
Laser Scanning ◽  
Spatial Information ◽  
Information Source ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Biochemical Properties ◽  
Dual Wavelength ◽  
Wavelength Scanning ◽  
Spatial Attributes

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.

Visualization of morphological details in congenitally malformed hearts: virtual three-dimensional reconstruction from magnetic resonance imaging

2003 ◽  
Vol 13 (5) ◽  
pp. 451-460 ◽  
Author(s):  
Thomas Sangild Sørensen ◽  
Erik Morre Pedersen ◽  
Ole Kromann Hansen ◽  
Keld Sørensen
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Real Time ◽  
Clinical Experience ◽  
Spatial Information ◽  
Three Dimensional ◽  
Three Dimensional Reconstruction ◽  
Resonance Imaging ◽  
Cardiac Malformations ◽  
Dimensional Reconstruction

In recent years, three-dimensional imaging has provided new opportunities for visualizing congenital cardiac malformations. We present the initial clinical experience using a recently implemented system, which employs some of new interactive, real-time, techniques. We show how three-dimensional rendering based on magnetic resonance imaging can provide detailed spatial information on both intrinsic and extrinsic cardiac relations, and hence how a virtual examination can potentially provide new means to a better understanding of complex congenital cardiac malformations.

scholarly journals The Human Dynamic Clamp reveals the fronto-parietal network linking real-time social coordination and cognition

2019 ◽  
Author(s):  
G. Dumas ◽  
Q. Moreau ◽  
E. Tognoli ◽  
J.A.S. Kelso
Keyword(s):  
Social Cognition ◽  
Social Behavior ◽  
Real Time ◽  
Dynamic Clamp ◽  
Sensorimotor Coordination ◽  
Self And Other ◽  
The Right ◽  
High Level ◽  
Sensorimotor Mechanisms ◽  
The Brain

AbstractHow does the brain allow us to interact with others, and above all how does it handle situations when the goals of the interactors overlap (i.e. cooperation) or differ (i.e. competition)? Social neuroscience has already provided some answers to these questions but has tended to treat high-level, cognitive interpretations of social behavior separately from the sensorimotor mechanisms upon which they rely. The goal here is to identify the underlying neural processes and mechanisms linking sensorimotor coordination and intention attribution. We combine the Human Dynamic Clamp (HDC), a novel paradigm for studying realistic social behavior between self and other in well-controlled laboratory conditions, with high resolution electroencephalography (EEG). The collection of humanness and intention attribution reports, kinematics and neural data affords an opportunity to relate brain activity to the behavior of the HDC as well as to what the human is doing. Behavioral results demonstrate that sensorimotor coordination influences judgements of cooperativeness and humanness. Analysis of brain dynamics reveals two distinct networks related to integration of visuo-motor information from self and other. The two networks overlap over the right parietal region, an area known to be important for interpersonal motor interactions. Furthermore, connectivity analysis highlights how the judgement of humanness and cooperation of others modulate the connection between the right parietal hub and prefrontal cortex. These results reveal how distributed neural dynamics integrates information from ‘low-level’ sensorimotor mechanisms and ‘high-level’ social cognition to support the realistic social behaviors that play out in real time during interactive scenarios.Significance StatementDaily social interactions require us to coordinate with others and to reflect on their potential motives. This study investigates the brain and behavioral dynamics of these two key aspects of social cognition. Combining high-density electroencephalography and the Human Dynamic Clamp (a Virtual Partner endowed with human-based coordination dynamics), we show first, that several features of sensorimotor coordination influence attribution of intention and judgement of humanness; second, that the right parietal lobe is a key integration hub between information related to self- and other-behavior; and third, that the posterior online social hub is functionally coupled to anterior offline brain structures to support mentalizing about others. Our results stress the complementary nature of low-level and high-level mechanisms that underlie social cognition.

scholarly journals Applicability of a 3D Laser Scanner for Characterizing the Spray Distribution Pattern of an Air-Assisted Sprayer

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
F. Javier García-Ramos ◽  
Alfredo Serreta ◽  
Antonio Boné ◽  
Mariano Vidal
Keyword(s):  
Air Flow ◽  
Sonic Anemometer ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Static Mode ◽  
Static Test ◽  
Axial Fans ◽  
Spray Distribution ◽  
The One ◽  
The Right

Three-dimensional (3D) laser technology has been tested for assessing the performance of air-assisted spraying. A static test using an air-assisted sprayer equipped with two axial fans (front and back) with opposing directions of rotation was developed. The sprayer was adjusted to spread water in a static mode, at a pressure of 10 bars, with four air volumetric flow rates. Measurements were performed using a Leica HDS6000 3D laser scanner. In addition, the flow and velocity of air generated by the air-assisted sprayer were measured using a hot-wire anemometer and a 3D sonic anemometer with the objective of estimating the influence of air flow on the spatial distribution of spray droplets. To carry out the analysis, all of the droplets detected by the laser were considered to be of the same size. The distribution of products was asymmetric when the machine only worked with the back fan, with 41% of the product distributed on the left side versus 59% on the right side, as referenced to the direction of the machine’s advance. This asymmetry was corrected when the machine functioned with the two fans activated. These spray data were concordant with the measured air flow generated by the machine in the different working conditions. For the different regulation settings of the machine, taking the vertical of the machine as 0°, the angular region comprised between 40° and 60° was the one that received the highest quantity of product. The increase of the air flow produced a greater distance of the product. For the highest air flow configuration, 99% of the product detected by the laser was detected within a distance of 16 m from the axis of the machine.

The Design and Realization of Real-Time Three-Dimensional Visualization System for Industrial Computed Tomography Based on GPU

2012 ◽  
Vol 268-270 ◽  
pp. 1706-1709
Author(s):  
Qian Li Wang ◽  
Jian Fu ◽  
Ren Bo Tan ◽  
Li Yuan Chen
Keyword(s):  
Computed Tomography ◽  
Real Time ◽  
Graphics Processing Unit ◽  
Three Dimensional ◽  
Processing Unit ◽  
Destructive Testing ◽  
Visualization System ◽  
Industrial Computed Tomography ◽  
Visualization Toolkit ◽  
Graphics Processing

Industrial computed tomography (ICT) is an advanced non-contact non-destructive testing technique and plays a key role in many fields. Low imaging efficiency is one of the drawbacks of ICT towards engineering applications. In this paper, we report the design and realization of real-time three-dimensional Visualization System for ICT based on visualization toolkit (VTK) and the graphics processing unit (GPU) technique. It greatly improves the imaging speed by developing the new techniques in three aspects such as image reconstruction, data compression and fast volume rendering with GPU and VTK. It will find applications in three-dimensional ICT systems.

scholarly journals Efficient protein tertiary structure retrievals and classifications using content based comparison algorithms

2007 ◽  
Author(s):  
◽  
Pin-Hao Chi
Keyword(s):  
Protein Structure ◽  
Real Time ◽  
High Throughput ◽  
High Efficiency ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Comparison Algorithms ◽  
High Level ◽  
Protein Structure Retrieval

Functionally important sites of proteins are potentially conserved to specific three-dimensional structural folds. To understand the structure-to-function relationship, life sciences researchers and biologists have a great need to retrieve similar structures from protein databases and classify these structures into the same protein fold. Traditional protein structure retrieval and classification methods are known to be either computationally expensive or labor intensive. In the past decade, more than 35000 protein structures have been identified. To meet the needs of fast retrieval and classifying high-throughput protein data, our research covers three main subjects: (1) Real-time global protein structure retrieval: We introduce an image-based approach that extracts signatures of three-dimensional protein structures. Our high-level protein signatures are then indexed by multi-dimensional indexing trees for fast retrieval. (2) Real-time global protein structure classification: An advanced knowledge discovery and data mining (KDD) model is proposed to convert high-level protein signature into itemsets for mining association rules. The advantage of this KDD approach is to effectively reveal the hidden knowledge from similar protein tertiary structures and quickly suggest possible SCOP domains for a newly-discovered protein. In addition, we develop a non-parametric classifier, E-Predict, that can rapidly assign known SCOP folds and recognize novel folds for newly-discovered proteins. (3) Efficient local protein structure retrieval and classification: We propose a novel algorithm, namely, the Index-based Protein Substructure Alignment (IPSA), that constructs a two-layer indexing tree to capture the obscured similarity of protein substructures in a timely fashion. Our research works exhibit significantly high efficiency with reasonably high accuracy and will benefit the study of high-throughput protein structure-function evolutionary relationships.

scholarly journals Real-Time Obstacle Avoidance for Manned/Unmanned Aircraft Cooperative System Based on Improved Velocity Obstacle Method

2020 ◽  
Vol 38 (2) ◽  
pp. 309-318
Author(s):  
Yue Li ◽  
Wei Han ◽  
Qingyang Chen ◽  
Yong Zhang
Keyword(s):  
Real Time ◽  
Obstacle Avoidance ◽  
Three Dimensional ◽  
Unmanned Aircraft ◽  
Cooperative System ◽  
Flight Mode ◽  
Multi Agent ◽  
The Difference ◽  
The Right ◽  
Velocity Obstacle

To adapt the autonomous level of agents in current, and to perform the advantages of multi-agent in air combat, the form of manned/unmanned aircraft cooperative system has gradually become a hot topic. To solve the issue of three-dimensional (3D) real-time obstacle avoidance, the 3D maneuvering obstacle model is established firstly based on the traditional velocity obstacle method. Then the flight mode is selected and the optimal obstacle avoidance plane is determined by setting the Right-of-way rules when the system encountering obstacles. Finally, the difference of obstacle avoidance plane, the feasibility of avoiding maneuvering obstacle and the effectiveness of obstacle avoidance of cooperative system are verified by several flight simulations. The results show that the proposed method can realize the avoidance of 3D maneuvering obstacle for manned/unmanned aircraft cooperative system safely and efficiently.

scholarly journals Multistage Polymerization Network for Multiperson Pose Estimation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yu-Fei Bai ◽  
Hong-Bo Zhang ◽  
Qing Lei ◽  
Ji-Xiang Du
Keyword(s):  
Pose Estimation ◽  
Information Exchange ◽  
Spatial Information ◽  
Complex Problem ◽  
Feature Maps ◽  
Low Level ◽  
Discriminative Feature ◽  
Level Information ◽  
Public Datasets ◽  
High Level

Multiperson pose estimation is an important and complex problem in computer vision. It is regarded as the problem of human skeleton joint detection and solved by the joint heat map regression network in recent years. The key of achieving accurate pose estimation is to learn robust and discriminative feature maps. Although the current methods have made significant progress through interlayer fusion and intralevel fusion of feature maps, few works pay attention to the combination of the two methods. In this paper, we propose a multistage polymerization network (MPN) for multiperson pose estimation. The MPN continuously learns rich underlying spatial information by fusing features within the layers. The MPN also adds hierarchical connections between feature maps at the same resolution for interlayer fusion, so as to reuse low-level spatial information and refine high-level semantic information to obtain accurate keypoint representation. In addition, we observe a lack of connection between the output low-level information and the high-level information. To solve this problem, an effective shuffled attention mechanism (SAM) is proposed. The shuffle aims to promote the cross-channel information exchange between pyramid feature maps, while attention makes a trade-off between the low-level and high-level representations of the output features. As a result, the relationship between the space and the channel of the feature map is further enhanced. Evaluation of the proposed method is carried out on public datasets, and experimental results show that our method has better performance than current methods.

scholarly journals VIRTUALIZING SUPER-COMPUTATION ON-BOARD UAS

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1291-1298 ◽  
Author(s):  
E. Salami ◽  
J. A. Soler ◽  
R. Cuadrado ◽  
C. Barrado ◽  
E. Pastor
Keyword(s):  
Real Time ◽  
High Performance ◽  
Unmanned Aerial Systems ◽  
Sensing Applications ◽  
Recent Developments ◽  
Level Information ◽  
Information Products ◽  
High Level ◽  
The Cost ◽  
Aerial Systems

Unmanned aerial systems (UAS, also known as UAV, RPAS or drones) have a great potential to support a wide variety of aerial remote sensing applications. Most UAS work by acquiring data using on-board sensors for later post-processing. Some require the data gathered to be downlinked to the ground in real-time. However, depending on the volume of data and the cost of the communications, this later option is not sustainable in the long term. This paper develops the concept of virtualizing super-computation on-board UAS, as a method to ease the operation by facilitating the downlink of high-level information products instead of raw data. Exploiting recent developments in miniaturized multi-core devices is the way to speed-up on-board computation. This hardware shall satisfy size, power and weight constraints. Several technologies are appearing with promising results for high performance computing on unmanned platforms, such as the 36 cores of the TILE-Gx36 by Tilera (now EZchip) or the 64 cores of the Epiphany-IV by Adapteva. The strategy for virtualizing super-computation on-board includes the benchmarking for hardware selection, the software architecture and the communications aware design. A parallelization strategy is given for the 36-core TILE-Gx36 for a UAS in a fire mission or in similar target-detection applications. The results are obtained for payload image processing algorithms and determine in real-time the data snapshot to gather and transfer to ground according to the needs of the mission, the processing time, and consumed watts.

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