https://github.com/iliasprc/four-wheeled-robotic-car

Navigation of robot car using Computer Vision techniques
https://github.com/iliasprc/four-wheeled-robotic-car

autonomous-robots line-follower robotics ros

Last synced: about 1 month ago
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Navigation of robot car using Computer Vision techniques

• Host: GitHub
• URL: https://github.com/iliasprc/four-wheeled-robotic-car
• Owner: iliasprc
• Created: 2018-07-14T08:17:24.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-09-29T13:10:15.000Z (about 1 year ago)
• Last Synced: 2023-09-29T17:10:33.141Z (about 1 year ago)
• Topics: autonomous-robots, line-follower, robotics, ros
• Language: C++
• Size: 4.92 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Four-Wheeled Robotic Car Navigation using Computer Vision Techniques

## Project Overview

This project, conducted as part of the MEng Thesis in the Department of Electrical Engineering and Computer Science at the University of Patras, showcases innovative applications of computer vision for autonomous navigation in a four-wheeled robotic car. The research primarily focuses on two key techniques: Line Following and Navigation with Aruco Markers. Through a combination of cutting-edge technology and advanced algorithms, this project demonstrates the feasibility of implementing real-time vision-based navigation in robotic systems.

## Line Folllowing

The Line Following module demonstrates the robot's ability to autonomously follow a predefined path. Utilizing sophisticated computer vision algorithms, the robot identifies and tracks lines on the ground, enabling it to maintain a steady course. This technology has wide-ranging applications in sectors like manufacturing, where automated vehicles can transport materials along designated routes with high precision and efficiency.

### Demo Video

[![Alt text](https://img.youtube.com/vi/B1neTxKbR9I/0.jpg)](https://www.youtube.com/watch?v=B1neTxKbR9I)

##  Navigation with Aruco Markers:

The Navigation with Aruco Markers module showcases the robot's capability to navigate based on Aruco markers, a type of augmented reality marker. By recognizing these markers, the robot accurately determines its position and orientation in the environment. This technique holds immense potential in fields such as robotics research, where robots need to operate in diverse and unstructured environments while maintaining accurate spatial awareness.

### Demo Video

[![Alt text](https://img.youtube.com/vi/BPHMxqLuH70/0.jpg)](https://www.youtube.com/watch?v=BPHMxqLuH70)

### Project Features:

Real-time Image Processing: The project employs real-time image processing techniques to ensure swift and accurate decision-making by the robotic car.

Precision and Accuracy: Through advanced algorithms, the robot achieves high precision in following lines and accurately interpreting Aruco markers, showcasing the project's technical sophistication.