https://www.udemy.com/course/ros2-path-planning-and-maze-solving-with-computer-vision
Mobile Robot Localization , Navigation and Motion Planning with Robot Operating System 2
What you'll learn: Build your own Self Driving Car in Simulation (ROS2) Learn to develop 4 Essential Self Drive features (Lane Assist, Cruise Control, Nav. T-Junc, Cross Intersections) Master ComputerVision techniques e.g. (Detection, Localization, Tracking) Deep Dive with Custom-built Neural Networks (CNN's) Requirements: Python basic Programming and Modules Description: This Course Contains ROS2 Based self-driving car through an RGB camera, created from scratch Self Drive Features: - Lane Assist - Cruise Control - T-Junction Navigation - Crossing Intersections Ros Package World Models Creation Prius OSRF gazebo Model Editing Nodes, Launch Files SDF through Gazebo Textures and Plugins in SDF Software Part : Perception Pipeline setup Lane Detection with Computer Vision Techniques Sign Classification using (custom-built) CNN Traffic Light Detection Using Haar Cascades Sign and Traffic Light Tracking using Optical Flow Rule-Based Control Algorithms Pre-Course Requirments Software Based Ubuntu 20.04 (LTS) ROS2 - Foxy Fitzroy Python 3.6 Opencv 4.2 Tensorflow 2.14 Skill Based Basic ROS2 Nodes Communication Launch Files Gazebo Model Creation Motivated mind :) Course Flow (Self-Driving [Development Stage]) We will quickly get our car running on Raspberry Pi by utilizing 3D models ( provided in the repository) and car parts bought from links provided by instructors. After that, we will interface raspberry Pi with Motors and the camera to get started with Serious programming. Then by understanding the concept of self-drive and how it will transform our near future in the field of transportation and the environment. Then we will perform a comparison between two SD Giants (Tesla & Waymo) ;). After that, we will put forward our proposal by directly talking you inside the simulation so that you can witness course outcomes yourself. Primarily our Self Driving car will be composed of four key features. 1) Lane Assist 2) Cruise Control 3) Navigating T-Junction 4) Crossing Intersection Each feature development will comprise of two parts a) Detection: Gathering information required for that feature b) Control: Proposing appropriate response for the information received Software Requirements Ubuntu 20.4 and ROS2 Foxy Python 3.6 OpenCV 4.2 TensorFlow Motivated mind for a huge programming ProjectWho this course is for:Engineers wanting to embark in the fields of Computer Vision, Artificial Intelligence and Robotics Who this course is for: Engineers wanting to embark in the fields of Computer Vision, Artificial Intelligence and Robotics
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