ROS2 Path Planning and Maze Solving with Computer Vision | Udemy [Update 06/2024]
English | Size: 8.57 GB
Genre: eLearning[/center]
Mobile Robot Localization , Navigation and Motion Planning with Robot Operating System 2
What you'll learn
Build your own Maze Solving Simulation (ROS2)
Write Search algorithms [A* , Dijikstra, Min Heap]
Computer Vision techniques e.g. (Detection, Segmentation)
Deep Dive with Custom-built Navigation Graphs
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 .
Custom Robot Creation
Gazebo and Rviz Integerations
Localization
Navigation
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
Who this course is for:
Robotics Researchers
Engineers wanting to embark in the fields of Computer Vision, Artificial Intelligence and Robotics
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