Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem.

Slides:



Advertisements
Similar presentations
CSE 424 Final Presentation Team Members: Edward Andert Shang Wang Michael Vetrano Thomas Barry Roger Dolan Eric Barber Sponsor: Aviral Shrivastava.
Advertisements

Project Title Here IEEE UCSD Overview Robo-Magellan is a robotics competition emphasizing autonomous navigation and obstacle avoidance over varied, outdoor.
COLORCOLOR A SET OF CODES GENERATED BY THE BRAİN How do you quantify? How do you use?
REU LEGO MINDSTORMS NXT SOCCER Kenneth Mendoza, Paul Balda, Abimilex Reverón & Mentor : Andres Buss Molina Department of Computer Science & Engineering.
Autonomous Vehicle Pursuit of Target Through Optical Recognition Vision & Image Science Laboratory, Department of Electrical Engineering,Technion Daniel.
Bohr Robot Group OpenCV ECE479 John Chhokar J.C. Arada Richard Dixon.
Abstract This project focuses on realizing a series of operational improvements for WPI’s unmanned ground vehicle Prometheus with the end goal of a winning.
Skills: selecting colors, specifying colors in HTML Concepts: combining red, green and blue light to generate colors, combining light versus combining.
Sponsors Mechanical Improvements Software The software is written in C++ and Python using the Robot Operating System (ROS) framework. The ROS tool, rviz,
Video enhances, dramatizes, and gives impact to your multimedia application. Your audience will better understand the message of your application.
Intelligent Ground Vehicle Competition 2006 Brigham Young University.
Computer Vision Introduction to Image formats, reading and writing images, and image environments Image filtering.
Autonomous Vehicle: Navigation by a Line Created By: Noam Brown and Amir Meiri Mentor: Johanan Erez and Ronel Veksler Location: Mayer Building (Electrical.
RIT - Department of Computer Engineering Winter 2006 Andrey Kozitsky Seth Kramer
Ch 1 Intro to Graphics page 1CS 367 First Day Agenda Best course you have ever had (survey) Info Cards Name, , Nickname C / C++ experience, EOS experience.
Contains 16,777,216 Colors. My Car is red My Car is red How do I add colors to my web page? Notepad Browser Works with the “Standard” colors: Red, Green,
Prepared by: - Mr. T.R.Shah, Lect., ME/MC Dept., U. V. Patel College of Engineering. Ganpat Vidyanagar. Digital Image Processing & Machine Vision – An.
Computer Vision. DARPA Challenge Seeks Robots To Drive Into Disasters. DARPA's Robotics Challenge offers a $2 million prize if you can build a robot capable.
Faculty of Sciences and Social Sciences HOPE Website Development Graphics Stewart Blakeway FML 213
© GCSE Computing Candidates should be able to:  explain the representation of an image as a series of pixels represented in binary  explain the need.
Welcome Topic: Pixels A.M.Meshkatur Rahman Class: vii Roll: 07.
Color. -Visual light -An integral part of the sculpture -Creates desired effect -Distinguish items -Strengthen interest.
TOPIC 4 INTRODUCTION TO MEDIA COMPUTATION: DIGITAL PICTURES Notes adapted from Introduction to Computing and Programming with Java: A Multimedia Approach.
Objective Understand concepts used to create digital graphics. Course Weight : 15% Part Three : Concepts of Digital Graphics.
Lesson 13 – Color and Typography. 2 Objectives Discuss basic color theory. Understand the color wheel. Understand how color is presented on a computer.
Digital Terminology. Bitmap A representation consisting of rows and columns of dots of a graphic image stored in computer memory. To display a bitmap.
1 © 2010 Cengage Learning Engineering. All Rights Reserved. 1 Introduction to Digital Image Processing with MATLAB ® Asia Edition McAndrew ‧ Wang ‧ Tseng.
Application in Computer Vision Final Project Nir Slakman, Oren Zur and Noam Ben-Ari.
Number Systems CIT Network Math
Color and Resolution Introduction to Digital Imaging.
CSC Computing with Images
Obstacle Avoidance using Machine Vision Joose Rautemaa
DIEGO AGUIRRE COMPUTER VISION INTRODUCTION 1. QUESTION What is Computer Vision? 2.
1 Computer Graphics Week2 –Creating a Picture. Steps for creating a picture Creating a model Perform necessary transformation Lighting and rendering the.
Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem.
Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem.
Presented By: ROLL No IMTIAZ HUSSAIN048 M.EHSAN ULLAH012 MUHAMMAD IDREES027 HAFIZ ABU BAKKAR096(06)
Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem.
Computer Vision Introduction to Digital Images.
DATA REPRESENTATION CHAPTER DATA TYPES Different types of data (Fig. 2.1) The computer industry uses the term “MULTIMEDIA” to define information.
Why a bitmap (.bmp), not a.jpg? If you cannot save a.bmp, make it an uncompressed.tif. Compression (of this 8-bit 397,000 pixel image): none (397kb memory)medium.
Color Web Design Professor Frank. Color Displays Based on cathode ray tubes (CRTs) or back- lighted flat-screen Monitors transmit light - displays use.
IEEE Robot Team Vision System Project Michael Slutskiy & Paul Nguyen ECE 533 Presentation.
Intro to Color Theory. Objectives Identify and discuss various color models including RGB, CMYK, Black/white and spot color. Investigate color mixing.
CISC 110 Day 3 Introduction to Computer Graphics.
Final Year Project. Project Title Kalman Tracking For Image Processing Applications.
Chapter 1: Image processing and computer vision Introduction
Augmented Reality and 3D modelling Done by Stafford Joemat Supervised by Mr James Connan.
PART TWO Electronic Color & RGB values 1. Electronic Color Computer Monitors: Use light in 3 colors to create images on the screen Monitors use RED, GREEN,
TOPIC 4 INTRODUCTION TO MEDIA COMPUTATION: DIGITAL PICTURES Notes adapted from Introduction to Computing and Programming with Java: A Multimedia Approach.
BINARY Toby Wilson. LEARNING OBJECTIVES  Be able to convert binary to denary  Be able to convert denary into binary  Be able to explain how computers.
Software Narrative Autonomous Targeting Vehicle (ATV) Daniel Barrett Sebastian Hening Sandunmalee Abeyratne Anthony Myers.
An Introduction to Digital Image Processing Dr.Amnach Khawne Department of Computer Engineering, KMITL.
Lesson 13 – Color and Typography. 2 Objectives Understand basic color theory. Understand the color wheel. Understand how color is presented on a computer.
Coin Recognition Using MATLAB - Emad Zaben - Bakir Hasanein - Mohammed Omar.
Day 3: computer vision.
Signal and Image Processing Lab
CSC391/691 Intro to OpenCV Dr. Rongzhong Li Fall 2016
The Colour of Light: Additive colour theory.
Milestone Five Florida Tech IGVC.
What do these words mean to you?
Chapter 1: Image processing and computer vision Introduction
Pixels.
Colors Computers build colors from Red, Green, and Blue; not Red, Blue, and Yellow. RGB = Red Green Blue Creating Colors Red + Blue = Purple No Red, No.
What Color is it?.
Coupled Horn-Schunck and Lukas-Kanade for image processing
Digital Image Processing
Basic Concepts of Digital Imaging
Non-numeric Data Representation
Jetson-Enabled Autonomous Vehicle
Presentation transcript:

Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem - Shane Brumbley - Faculty Sponsor Dr. Eraldo Ribeiro - Project Website

Introduction Designing Control Software for autonomous obstacle course navigating vehicle. –Must navigate from waypoint to waypoint –Must use LIDAR, GPS, Digital Compass, and Camera to determine movement around the course –Must stay within lane lines and avoid obstacles in the completion lane

Refactoring Progress ~99% Done Will continue as new code is written Uses Hungarian notation Consistent code style throughout Reorganized as necessary

Example

Things to Change

Current State of Navigation Roughly 30% done Vehicle has some “bugs” Grouping obstacles may be the problem Random, bad LiDAR data

What’s to Come for Navigation Improve Think() Improve CostFunction() Integrate image processing Handle bad data Test

Detecting Color Need to detect Yellow and White All color has Red, Green, and Blue values between 0 and 255 each. A combination of these three colors yields a shade. To detect color, you must look for a certain RGB combination.

Handling White White occurs when all values of RGB are 255. In order to detect white, we set up a range, usually of 35 units. In our demo, if a pixel is determined to be white, we will change the blue value to 0(Zero)

Handling Yellow Yellow occurs at red 255 and green 255, at a given range of 35 units each. Because a blue of 255 equals white, any blue value will create a lighter shade of yellow. In our demo, any yellow pixel is set to true yellow and non-yellow non-white pixels create are set to black.

Line Detection By Using Emgu CV library (Open CV for C#) and the camera attached on the laptop – –We use this library for some Computer Vision functions. – –Detect lines and edges in an image – –Easy and fast for detecting lines and edges in a video image – –Produce and update the image frame Detect lines by Hough transform Algorithm – –Available in the Emgu CV library – –Required conversion from Image to Bitmap to display the image on the picture box

Demo of Line Detection

Milestone 4 Task Matrix

Questions, Comments, or Concerns?