ROS2 Path Planning and Maze Solving with Computer Vision | Udemy

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  🙂