A real-time low-cost marker-based multiple camera tracking solution for virtual reality applications

2009 ◽  
Vol 5 (2) ◽  
pp. 121-128 ◽  
Author(s):  
Pedro Carlos Santos ◽  
André Stork ◽  
Alexandre Buaes ◽  
Carlos Eduardo Pereira ◽  
Joaquim Jorge
Author(s):  
Manuel Gonza´lez ◽  
Alberto Luaces ◽  
Daniel Dopico ◽  
Javier Cuadrado

The actuation of hydraulic excavators is a complex and not intuitive task which requires long and costly training periods, since the qualification of the operator has a significant impact in productivity and safety. Simulation-based training combined with virtual reality is becoming a competitive alternative to traditional training to reduce costs and risks in the instruction of excavator operators. Several excavator training simulators have been developed, but none of them features a dynamic model of the machine complete enough to simulate all the maneuvers performed in the daily work of real excavators. The authors have applied real-time simulation techniques from multibody system dynamics to develop a full 3D physics-based excavator simulator made up of 14 rigid bodies with 17 degrees of freedom. The simulation engine includes a custom collision detection algorithm and detailed tire force and contact force models. Terrain excavation and bucket loading and unloading are also simulated. The resulting model delivers realistic real-time behavior and can simulate common events in real excavators: slipping on slope terrains, stabilizing the machine with the blade or the outriggers, using the arm for support or impulsion to avoid obstacles, etc. The simulator console has a semi-immersive virtual reality interface that emulates the excavator cabin. The operator console imitates most of the controls of the real machine cabin using low-cost standard USB input devices: steering wheel, 2 joystiks with the standard excavator functions and 2 pedals. A tactile screen replicates the digital control panel of the excavator, which lets the operator control different machine settings. A hard shell hemispherical dome of 2 m diameter is used to project the subjective view from the operator’s position. The resulting simulator, which can run in a standard PC due to its high computational efficiency, can reproduce almost all the maneuvers performed by real excavators.


2019 ◽  
Vol 10 (1) ◽  
pp. 160-166 ◽  
Author(s):  
Vu Trieu Minh ◽  
Nikita Katushin ◽  
John Pumwa

AbstractThis project designs a smart glove, which can be used for motion tracking in real time to a 3D virtual robotic arm in a PC. The glove is low cost with the price of less than 100 € and uses only internal measurement unit for students to develop their projects on augmented and virtual reality applications. Movement data from the glove is transferred to the PC via UART DMA. The data is set as the motion reference path for the 3D virtual robotic arm to follow. APID feedback controller controls the 3D virtual robot to track exactly the haptic glove movement with zero error in real time. This glove can be used also for remote control, tele-robotics and tele-operation systems.


2021 ◽  
Vol 6 (1) ◽  
pp. 71
Author(s):  
Seul-Bit-Na Koo ◽  
Hyeon-Gyu Chi ◽  
Ji-Sung Park ◽  
Jong-Dae Kim ◽  
Chan-Young Park ◽  
...  

The general polymerase chain reaction (PCR) amplifies DNA and analyzes the amplification results of the quantified DNA. Recently, real-time PCR has been developed to detect DNA amplification in various ways. The conventional camera-based system is too expensive and difficult to reduce device size. In this paper, we propose a low-cost, compact fluorescence detection system for real-time PCR systems using an open platform camera. To simplify the optics, four low-cost small cameras were fixedly placed, and the entire tube was divided into four quadrants to minimize the field of view. In addition, an effective image processing method was used to compensate. The proposed system measured the fluorescence detection performance on the basis of the amount of DNA using various fluorescent substances.


2007 ◽  
Vol 32 (2) ◽  
pp. 7-16
Author(s):  
Ming Tang ◽  
Dihua Yang

Having been a promising visualization tool since 1950s, ironically, virtual reality is not widely used in the architectural design and evaluation process due to several constrains, such as the high cost of equipments and advanced programming skills required. This paper described the collaboration between design computing courses and architecture design studios that have been taught at Savannah College of Art and Design (SCAD) in 2004 and 2005. These courses explored several practical methods to integrate Low Cost Virtual Reality Aided Design (LC-VRAD) in the architectural design process. As a summary of the collaboration, this paper refers to three main aspects: (1) How to use game engine to design an affordable VR system in the ordinary studio environment. (2) How to integrate VR, into the design process, not only as a visualization tool, but also as a design instrument. (3) How to evaluate different methods of representing architectural models based on the efficiency of workflow, rendering quality and users' feedback. Support by the Game and Interactive Design Department at SCAD, students in the School of Building Arts implemented two Low Cost VRAD methods in various design phases, starting from site analysis, schematic design, design development to the final presentation. Two popular game engines, Epic Game's Unreal engine and Director MX's Shockwave engine, were introduced to students to visualize their project in real-time. We discussed computer-aided design theories including the application of VR, as well as digital computing and human computer interaction. At the end of each quarter, feedbacks from students and faculties were collected and analyzed. These methods were revised and improved consistently across 2004 and 2005 academic year.


Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).


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