Embedded System Based Target Tracking

2012 ◽  
Vol 468-471 ◽  
pp. 1605-1608
Author(s):  
Qi Yuan Sun ◽  
Liu Sheng Li ◽  
Zuo Liang Cao
Keyword(s):  
Mobile Robot ◽  
Embedded System ◽  
Particle Filter ◽  
Target Tracking ◽  
Real Time ◽  
Energy Cost ◽  
Low Energy ◽  
Experimental Results ◽  
Moving Target ◽  
The Real

A mobile robot based on embedded system can meet the requirement of low energy cost and miniaturization. An embedded system for moving target tracking is designed in this paper. By combining with wavelet transmission, an improved algorithm of particle filter with wavelet particles is proposed for tracking maneuver target, and then a scheme of optimization is also proposed to enhance the real-time property of the system. Experimental results show that the system can be suitable for real-time target tracking applications.

Optimization and Realization of Target Tracking Algorithm Based on Embedded System

2012 ◽  
Vol 468-471 ◽  
pp. 2352-2356
Author(s):  
Qi Yuan Sun ◽  
Lei Ma ◽  
Zuo Liang Cao
Keyword(s):  
Mobile Robot ◽  
Embedded System ◽  
Particle Filter ◽  
Target Tracking ◽  
Real Time ◽  
Vision System ◽  
High Reliability ◽  
Tracking Algorithm ◽  
Real Time Processing ◽  
Particle Filter Algorithm

Target tracking algorithm is used widely in many fields, such as robot vision system, intelligent surveillance and medicine, but computational complexity and lack of dedicated embedded system for real-time processing have affected its application. This paper presents a method that combines embedded system, smart camera and mobile robot for detecting and tracking the moving targets. On the basis of particle filter algorithm, mean shift embedded particle filter algorithm is proposed and implemented on embedded platform with ARM+DSP dual core framework. At last, the whole system is optimized to improve the real-time property. The proposed method has a very powerful data processing ability, which can offer a high reliability for the navigation of a mobile robot.

scholarly journals Applications based on electromyography sensors

2019 ◽  
Vol 29 ◽  
pp. 02007
Author(s):  
Robert Kristof ◽  
Cristian Moldovan ◽  
Valentin Ciupe ◽  
Inocenţiu Maniu ◽  
Magdalena Banda
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Industrial Robot ◽  
Experimental Results ◽  
Real Time Control ◽  
The Real ◽  
Time Control ◽  
Myo Armband ◽  
Tracked Mobile Robot

This paper presents our work regarding two different applications that use the electromyography sensors incorporated in the Thalmic Labs Myo Armband. The first application is about the HumanMachine Interface (HMI) for controlling an industrial robot bycreating the environment for the user to control a robot’s gripper position just by moving his arm. The second application refers to the real time control of a tracked mobile robot that is built with the Arduino development board. For each application thesystem design and the experimental results are presented.

An Improved Trace Method for Moving Target under Occlusion

2014 ◽  
Vol 672-674 ◽  
pp. 1931-1934
Author(s):  
Yu Bing Dong ◽  
Guang Liang Cheng ◽  
Ming Jing Li
Keyword(s):  
Mathematical Model ◽  
Target Tracking ◽  
Difficult Problem ◽  
Block Matching ◽  
Experimental Results ◽  
Polar Coordinates ◽  
Moving Target ◽  
Trajectory Prediction ◽  
Tracking Method

Occlusion is a difficult problem to be solved in the process of target tracking. In order to solve the problem of occlusion, a new tracking method combined with trajectory prediction and multi-block matching is presented and studied,and a mathematical model of trajectory prediction of moving target is established in polar coordinates and verified through some experiments. The experimental results show that the new tracking method can be better to trace and forecast the moving target under occlusion.

Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data

2015 ◽  
Vol 6 (2) ◽  
pp. 88-116
Author(s):  
Abouzahir Mohamed ◽  
Elouardi Abdelhafid ◽  
Bouaziz Samir ◽  
Latif Rachid ◽  
Tajer Abdelouahed
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Particle Filter ◽  
Real Time ◽  
Autonomous Navigation ◽  
Hardware In The Loop ◽  
Heterogeneous Architectures ◽  
Localization And Mapping ◽  
Embedded Applications ◽  
Robotic Applications

The improved particle filter based simultaneous localization and mapping (SLAM) has been developed for many robotic applications. The main purpose of this article is to demonstrate that recent heterogeneous architectures can be used to implement the FastSLAM2.0 and can greatly help to design embedded systems based robot applications and autonomous navigation. The algorithm is studied, optimized and evaluated with a real dataset using different sensors data and a hardware in the loop (HIL) method. Authors have implemented the algorithm on a system based embedded applications. Results demonstrate that an optimized FastSLAM2.0 algorithm provides a consistent localization according to a reference. Such systems are suitable for real time SLAM applications.

The Method for Real-Time Length Measurement of Fiber Winding

2013 ◽  
Vol 380-384 ◽  
pp. 919-922
Author(s):  
Chen Xia Guo ◽  
Rui Feng Yang
Keyword(s):  
Real Time ◽  
Detection Algorithm ◽  
Moving Target ◽  
Fiber Optic Gyroscope ◽  
Optical Encoder ◽  
The Real ◽  
Time Length ◽  
Fiber Coil ◽  
Fiber Winding ◽  
Coil Winding

The paper discusess mainly how to accurately measure the real-time length of fiber optic gyroscope sensing coil (fiber coil) in the process of FOG coil winding. First, using the improved moving target detection algorithm to process the fiber images collected by machine vision. Secondly, using software algorithm to calculate the real-time radius of fiber winding. Finaly, combining the incremental optical encoder with real-time radius to calculate real-time winding length of fiber coil.

Applications of Distributed Parallel Real Time Database on Power Grid

2013 ◽  
Vol 816-817 ◽  
pp. 488-492
Author(s):  
Li Xin Li ◽  
Wei Zhou ◽  
Qi Qiang Sun ◽  
Jiao Dai ◽  
Ji Zhong Han ◽  
...  
Keyword(s):  
Data Management ◽  
Real Time ◽  
Management System ◽  
Power Grid ◽  
Database Design ◽  
Experimental Results ◽  
Data Management System ◽  
Meta Data ◽  
The Real ◽  
Real Time Database

In order to make the real time database more suitable for the computing features, this article points to the distributed and parallel real time database design and architecture. First, a mapping table from table file to machine nodes is established, and then can use meta-data management system to store and manage the mapping table to meet the characteristics of high concurrent access. The whole network computation can access the unified interface provided by the real-time database, retrive data from each node, then collect the data. Experimental results show that this study and the systems designed can meet the computing requirements of a unified whole network.

Implementation of the Particle Filter in an embedded system for the localization of a differential mobile robot

2018 ◽  
Author(s):  
Luciano L.S. Fortes ◽  
Lucas M. Ayres ◽  
Eduardo M. Rocha ◽  
Marco A.S.L. Cuadros ◽  
Joabe R. da Silva ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Embedded System ◽  
Particle Filter

Based on the Airborne SAR - ATI - GMTI System Research

2013 ◽  
Vol 380-384 ◽  
pp. 3938-3941 ◽  
Author(s):  
Wei Dong Zhang ◽  
Nuan Song ◽  
Yi Wu
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Moving Target ◽  
System Research ◽  
The Real ◽  
Dual Channel ◽  
Movement Parameter ◽  
Sar Data ◽  
Airborne Sar ◽  
Interference Phase

The actual airborne dual-channel data is disposed to indicate the moving target by ATI. In order to solve the problems caused by the unideal movement in the flight and other engineering factors which influence the GMTI, the paper presents the method to compensate the interference phase base on calculate the phase centroid of every sub-image. Besides, this paper simplifies some data processing to realize the real-time GMTI and improves the efficiency. With this method, the actual SAR data is proceeded to get the targets position and movement parameter. Results prove the validity of the approach.

Target Tracking Based Adaptive Particle Filter in Binary Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 2281-2287
Author(s):  
Ling Dong Su ◽  
Ming Yue Zhai ◽  
Zhi Yu Zhu
Keyword(s):  
Wireless Sensor Network ◽  
Particle Filter ◽  
Target Tracking ◽  
Real Time ◽  
Sensor Network ◽  
Particle Filtering ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Local Estimate ◽  
Real Time Tracking

Since real-time and communication amount is crucial for the wireless sensor network target tracking, the performance of target tracking in the wireless sensor network is critically depended on real-time and communication amount reduction. This paper presents a target tracking method based on distributed adaptive particle filtering in binary wireless sensor network. Based on dynamic clustering, the adaptive particle filter receives the observations from children nodes and formulates the local estimate with the cluster head as the processing center. Simulation results show that the method can effectively improve the real-time tracking and reduce communication amount.

Sign in / Sign up

Export Citation Format

Share Document