ROS2 Path Planning and Maze Solving with Computer Vision

Mobile Robot Localization , Navigation and Motion Planning with Robot Operating System 2

ROS2 Path Planning and Maze Solving with Computer Vision
ROS2 Path Planning and Maze Solving with Computer Vision

ROS2 Path Planning and Maze Solving with Computer Vision udemy course free download

Mobile Robot Localization , Navigation and Motion Planning with Robot Operating System 2

This course is focus on Maze Solving behavior of robot In a Simulation based on ROS2. Computer Vision is the key focus with integrated important robotics algorithms of Motion Planning . The type of robot we will be using is Differential Drive Robot with a caster wheel . Course is structured with below main headings .

  1. Custom Robot Creation

  2. Gazebo and Rviz Integerations

  3. Localization

  4. Navigation

  5. Path Planning

From our robot to last computer vision Node ,we will create every thing from scratch . Python Object Oriented programming practices will be utilized for better development.


Learning Outcomes

- Simulation Part

  • Creation Custom Robot Design in Blender ( 3D modeling )

  • Bringing Maze Bot into ROS Simulation powered by Gazebo and RVIZ

  • Drive your robot with Nodes

  • Add Sensor for better perception of Environment

  • Build different Mazes to be solved

- Algorithm Part

  • Localization with Fore and Back ground extraction

  • Mapping with Graphs Data Structure

  • Path Planning with

    • A* search

    • Dijikstra

    • DFS Trees

    • Min Heap

  • Navigation while avoiding Obstacles and GTG behavior


Pre-Course Requirments

Software Based

  • Ubuntu 20.04 (LTS)

  • ROS2 - Foxy Fitzroy

  • Python 3.6

  • Opencv 4.2

Skill Based

  • Basic ROS2 Nodes Communication

  • Launch Files

  • Gazebo Model Creation

  • Motivated mind :)

All the codes for reference are available on git hub repository of this course .

Get a good idea by going through all of our free previews available and feel free to Contact in case of any confusion  :)