Center-Oriented Aiming Strategy for Heliostat with Spinning-Elevation Tracking Method

2022 ◽  
pp. 1-21
Author(s):  
Sainath Waghmare ◽  
Bhalchandra P Puranik
Keyword(s):  
Ray Tracing ◽  
Tracking System ◽  
Substantial Reduction ◽  
Tracking Method ◽  
Field Center ◽  
Axis Of Rotation ◽  
Center Point

Abstract Spinning-Elevation (SE) tracking system produces a decent image on the receiver surface; however, it is subjected to large variations in tracking speed. In this research, a Graphical Ray Tracing (GRT) model for Center-Oriented Spinning-Elevation (COSE) tracking method is developed to evaluate tracking angles. Instead of a target, a heliostat is pointed towards the on-field center point of the tower. Therefore, a spinning-axis of rotation is a line joining a heliostat, and a center of the tower and elevation-axis is perpendicular to it. This aiming strategy has shown a substantial reduction in rotations of spinning-motor. In contrast, the elevation-motor runs at slightly higher rotations than the target-oriented SE method for the same application. Also, COSE tracking method obtains better shape of the reflected image with less aberration on the receiver surface as compared to SE and the traditional Azimuth-Elevation (AE) method.

Research on Underwater Target Tracking Based on Contour Detection

2011 ◽  
Vol 317-319 ◽  
pp. 890-896
Author(s):  
Ming Jun Zhang ◽  
Yuan Yuan Wan ◽  
Zhen Zhong Chu
Keyword(s):  
Prediction Model ◽  
Target Tracking ◽  
Tracking System ◽  
Contour Detection ◽  
Motion Prediction ◽  
Moving Target ◽  
Contour Extraction ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Underwater Target

The traditional centroid tracking method over-relies on the accuracy of segment, which easily lead to loss of underwater moving target. This paper presents an object tracking method based on circular contour extraction, combining region feature and contour feature. Through the correction to circle features, the problem of multiple solutions causing by Hough transform circle detection is avoided. A new motion prediction model is constructed to make up the deficiency that three-order motion prediction model has disadvantage of high dimension and large calculation. The predicted position of object centroid is updated and corrected by circle contour, forming prediction-measurement-updating closed-loop target tracking system. To reduce system processing time, on the premise of the tracking accuracy, a dynamic detection method based on target state prediction model is proposed. The results of contour extraction and underwater moving target experiments demonstrate the effectiveness of the proposed method.

A novel tracking system for human following robots with fusion of MMW radar and monocular vision

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yipeng Zhu ◽  
Tao Wang ◽  
Shiqiang Zhu
Keyword(s):  
Sensor Fusion ◽  
Tracking System ◽  
Cost Effective ◽  
Point Clouds ◽  
Human Detection ◽  
Multimodal Fusion ◽  
Target Person ◽  
Fusion Algorithm ◽  
Content Type ◽  
Tracking Method

Purpose This paper aims to develop a robust person tracking method for human following robots. The tracking system adopts the multimodal fusion results of millimeter wave (MMW) radars and monocular cameras for perception. A prototype of human following robot is developed and evaluated by using the proposed tracking system. Design/methodology/approach Limited by angular resolution, point clouds from MMW radars are too sparse to form features for human detection. Monocular cameras can provide semantic information for objects in view, but cannot provide spatial locations. Considering the complementarity of the two sensors, a sensor fusion algorithm based on multimodal data combination is proposed to identify and localize the target person under challenging conditions. In addition, a closed-loop controller is designed for the robot to follow the target person with expected distance. Findings A series of experiments under different circumstances are carried out to validate the fusion-based tracking method. Experimental results show that the average tracking errors are around 0.1 m. It is also found that the robot can handle different situations and overcome short-term interference, continually track and follow the target person. Originality/value This paper proposed a robust tracking system with the fusion of MMW radars and cameras. Interference such as occlusion and overlapping are well handled with the help of the velocity information from the radars. Compared to other state-of-the-art plans, the sensor fusion method is cost-effective and requires no additional tags with people. Its stable performance shows good application prospects in human following robots.

scholarly journals Bayesian Estimation-Based Pedestrian Tracking in Microcells

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yoshiaki Taniguchi ◽  
Masahiro Sasabe ◽  
Satoshi Aihara ◽  
Hirotaka Nakano
Keyword(s):  
Time Series ◽  
Combinatorial Optimization ◽  
Bayesian Estimation ◽  
Tracking System ◽  
Mobility Model ◽  
Sensor Nodes ◽  
Video Sequences ◽  
Pedestrian Tracking ◽  
Tracking Method ◽  
Success Ratio

We consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect pedestrian arrival and departure events. In this paper, we focus on pedestrian tracking in microcells. First, we investigate actual pedestrian trajectories in a microcell on the basis of observations using video sequences, after which we prepare a pedestrian mobility model. Next, we propose a method for pedestrian tracking in microcells based on the developed pedestrian mobility model. In the proposed method, we extend the Bayesian estimation to account for time-series information to estimate the correspondence between pedestrian arrival and departure events. Through simulations, we show that the tracking success ratio of the proposed method is increased by 35.8% compared to a combinatorial optimization-based tracking method.

scholarly journals Solar Ray Tracing Analysis to Determine Energy Availability in a CPC Designed for Use as a Residential Water Heater

2017 ◽  
Author(s):  
Miguel Terrón-Hernández ◽  
Manuel I. Peña-Cruz ◽  
J. G. Carrillo ◽  
Ulises Diego-Ayala ◽  
Vicente Flores
Keyword(s):  
Ray Tracing ◽  
Tracking System ◽  
Low Cost ◽  
Energy Availability ◽  
Water Heater ◽  
Available Energy ◽  
And Performance ◽  
Efficient Option ◽  
Prototype Design ◽  
Residential Water

Compound parabolic concentrators are relevant systems used in solar thermal technology. With adequate tailoring, they can be used as an efficient and low-cost alternative in residential water applications. This work presents a simulation study using a ray tracing methodology. With this technique we simulate the interaction between solar rays and solar concentrator to quantify the amount of energy that impinges on the receiver at a particular time. Energy availability is evaluated in a comparison of two configurations: stationary at 21° throughout the year and multi position setup; tilted with respect to the horizontal depending on three seasonal positions: 0° for summer, 16° for spring / autumn and 32° for winter, with the objective of increasing the amount of available energy in each season. The fact that a tracking system can be dispensed with also represents an economical option for the proposed application. The results showed that at 21°, the proposed system works satisfactorily; however, by carrying out the selected angular adjustments, the overall energy availability increased by 22%, resulting in a more efficient option. The methodology developed herein proved to be a valuable tool for prototype design and performance evaluation.

scholarly journals Pembuatan Alat Tracking Artefak pada Museum Menggunakan Modul GSM Berbasis Mikrokontroler dan Short Massage System.

2019 ◽  
Vol 3 (01) ◽  
pp. 18-24
Author(s):  
Irzan Marza
Keyword(s):  
Tracking System ◽  
General Science ◽  
Tracking Method ◽  
Research Activities ◽  
A Value ◽  
Historical Objects

The museum is in charge of providing facilities for these research activities for anyone, in addition to the museum in charge of carrying out the research activities themselves and disseminating the results of the research to the development of general science. However, in reality there is still the fact that cases of missing historical objects have a value of up to millions of rupiah. This study aims to create a tracking system that is able to track artifacts in the museum using the BTS system. Therefore, the author will make a tool that can track the position of the artifact with the Tracking method. The design of the study that the author will adopt from the above problem is "Making an Artifact Tracking Tool at the Museum Using a Microcontroller and Short Massage System-Based GSM Module".

Multi-object tracking using deformable convolution networks with tracklets updating

2019 ◽  
Vol 17 (06) ◽  
pp. 1950042 ◽  
Author(s):  
Yuanping Zhang ◽  
Yuanyan Tang ◽  
Bin Fang ◽  
Zhaowei Shang
Keyword(s):  
Object Tracking ◽  
Tracking System ◽  
Sampling Strategy ◽  
Geometric Transformation ◽  
Histogram Of Oriented Gradient ◽  
Tracking Method ◽  
Sampling Locations ◽  
Deep Networks ◽  
Background Clutter ◽  
Appearance Changes

Many multi-object tracking methods have been proposed to solve the computer vision problem which has been attracting significant attentions because of the significant appearance changes caused by deformation, abrupt motion, background clutter and occlusion. In this paper, hybrid deformable convolution neural networks with frame-pair input and deformable layers for multi-object tracking are presented. The object tracking method trained using two successive frames can predict the centers of searching windows as the locations of tracked targets to improve the accuracy and robustness of object tracking. Histogram of Oriented Gradient and CNN features are extracted as appearance features to measure similarities between objects. Kalman filter and Hungarian algorithm are used to create tracklets association which indicates the location and the trajectories of tracked targets. To solve the problem of object transformation, we construct a novel sampling strategy for off-line training with the idea of augmenting the special sampling locations in the convolution layers and pooling layers with additional offsets. Experiments on the popular challenging datasets show that the proposed tracking system performs on par with recently developed generic multi-object tracking methods, but effective for dense geometric transformation objects and with much less memory. In addition, the proposed tracking system can run in a speed of over 75 (24) fps with a GPU (CPU), much faster than most deep networks-based trackers.

Modeling and Sensitivity Analysis of Laser Tracking Systems by Skew-Ray Tracing Method

2004 ◽  
Vol 127 (3) ◽  
pp. 654-662 ◽  
Author(s):  
Psang Dain Lin ◽  
Chia-Hung Lu
Keyword(s):  
Sensitivity Analysis ◽  
Ray Tracing ◽  
Tracking System ◽  
Tracking Systems ◽  
Position Measurement ◽  
Ray Tracing Method ◽  
Laser Tracking ◽  
Corner Cube ◽  
Alignment Errors ◽  
Tracing Method

Laser tracking systems, such as the Leica LTD 500, are used for precision position measurement of large or distant objects, for example, the alignment of aircraft wings or bridge girders during assembly. A laser tracker’s performance is theoretically better than other common metrology equipment, such as coordinate measuring machines (CMMs). It is desirable that a flexible laser tracking system replaces the standard CMM, but measurement accuracy is highly dependent on the accuracy of its rotating mirror mechanism and its link dimension variance during tracker manufacture and assembly. Therefore this study presents a skew-ray tracing method for modeling and sensitivity analysis of laser tracking systems. First, the geometric relations of position-detector and interferometer readings are derived in terms of the laser tracker’s parameters using skew-ray tracing method. Effects of corner-cube alignment errors on sensor readings are also investigated theoretically, and it is found that misalignment of the corner-cube causes errors in path length and, therefore, misestimation of distance. Effects of mirror mechanism dimension errors are also investigated by sensitivity analysis. This study will be of use to theoretical and practical studies involving the modeling, design, and use of laser tracking systems and similar devices.

scholarly journals The application of image processing for Human-Computer Interface (HCI) using the Eye

2021 ◽  
Vol 2120 (1) ◽  
pp. 012030
Author(s):  
J K Tan ◽  
W J Chew ◽  
S K Phang
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Eye Gaze ◽  
Gaze Tracking ◽  
Tracking Method ◽  
Infrared Rays ◽  
Mouse Pointer ◽  
Hand Disability ◽  
Enzyme Denaturation ◽  
Human Eyes

Abstract The field of Human-Computer Interaction (HCI) has been developing tremendously since the past decade. The existence of smartphones or modern computers is already a norm in society these days which utilizes touch, voice and typing as a means for input. To further increase the variety of interaction, human eyes are set to be a good candidate for another form of HCI. The amount of information which the human eyes contain are extremely useful, hence, various methods and algorithm for eye gaze tracking are implemented in multiple sectors. However, some eye-tracking method requires infrared rays to be projected into the eye of the user which could potentially cause enzyme denaturation when the eye is subjected to those rays under extreme exposure. Therefore, to avoid potential harm from the eye-tracking method that utilizes infrared rays, this paper proposes an image-based eye tracking system using the Viola-Jones algorithm and Circular Hough Transform (CHT) algorithm. The proposed method uses visible light instead of infrared rays to control the mouse pointer using the eye gaze of the user. This research aims to implement the proposed algorithm for people with hand disability to interact with computers using their eye gaze.

An Improved Algorithm on Adaptive KLT Vision Tracking

2013 ◽  
Vol 631-632 ◽  
pp. 1270-1275
Author(s):  
Yuan Min Liu ◽  
Lian Fang Tian
Keyword(s):  
State Of The Art ◽  
Tracking System ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Feature Points ◽  
Backward Error ◽  
Tracking Method ◽  
Adaptive Tracking ◽  
Conventional Methods ◽  
Measurement Validity

In view of the shortage of the KLT (Kanade-Lucas-Tomasi) tracking algorithm, an improved adaptive tracking method based on KLT is proposed in this paper, in which a kind of filtering mechanism is applied to decrease the effects of noise and illumination on tracking system. In order to eliminate the error of tracking, the strategies based on forward-backward error and measurement validity are utilized properly. However, because the approach to forward-backward error makes the feature points reduce, which leads to tracking failure especially when the shapes of object change, a method for appending the feature points is introduced. Experimental results indicate that the method presented in this paper is state of the art robustness in our comparison with related work and demonstrate improved generalization over the conventional methods.

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