ROS2 Path Planning and Maze Solving with Computer Vision

ROS2 Path Planning and Maze Solving with Computer Vision

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  :)

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

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What you will learn

• Build your own Maze Solving Simulation (ROS2)
• Write Search algorithms [A* , Dijikstra, Min Heap]
• Computer Vision techniques e.g. (Detection, Segmentation)

Rating: 4.4

Level: Intermediate Level

Duration: 9.5 hours

Instructor: Muhammad Luqman