كورس أساسيات الراسبيري باي
كورس Object detection and AI مع الراسبيري باي
كورس ال ROS and SLAM Robotics
Getting Started with Raspberry Pi
What is Raspberry Pi? Overview and features
Installing Raspberry Pi OS
Initial setup: Display, keyboard, mouse, and Wi-Fi
Basic Linux Commands
Introduction to Linux terminal
File system navigation and management
Installing software via apt and pip
Getting Started with Linux
What is Linux? Overview and key features
Understanding the Raspberry Pi OS (Debian-based)
Practical: Explore the Raspberry Pi desktop and terminal
Basic Linux Commands
Navigating the file system
Creating, moving, and deleting files and directories
Viewing file contents
Setting Up Python on Raspberry Pi
Installing Python 3 and pip
Using Python IDEs: Thonny, VS Code, or the terminal
Python Basics
Data types, variables, and operators
Control flow and loops
Functions and modules
GPIO Programming with Python
Using the RPi.GPIO library for pin control
Input and output with buttons and LEDs
Interfacing Sensors and Actuators
Using libraries for sensors
Controlling motors with Python
I2C, SPI, and UART Communication
Using libraries for I2C and SPI devices
Serial communication
Image representation and processing
Color spaces (RGB, HSV, Grayscale)
Image filtering techniques
Histogram of oriented gradients (HOG)
OpenCV installation on Raspberry Pi
Image reading and manipulation
Basic image processing techniques
Edge detection algorithms
Haar Cascades
Viola-Jones object detection framework
Training custom cascades
Face and feature detection
YOLO (You Only Look Once)
Real-time object detection architecture
Different YOLO versions (v3, v4, v5)
Performance optimization
SSD (Single Shot Detector)
Multi-scale feature mapping
Anchor box concepts
Implementation strategies
TensorFlow Lite integration
Model conversion techniques
Performance benchmarking
Raspberry Pi optimization
Lane Detection
Perspective transformation
Color thresholding
Hough transform
Curve fitting algorithms
Pedestrian Detection
Machine learning models
Real-time tracking
Safety distance calculation
Obstacle Avoidance
Depth estimation techniques
Sensor fusion
Decision-making algorithms
Multi-object tracking
Event logging
Notification systems
Cloud integration
Navigation algorithms
Sensor data fusion
Path planning
Collision prediction
Implement vehicle-to-vehicle communication
Develop real-time data exchange protocols
Create cooperative safety applications
Develop vehicle-to-infrastructure communication
Create smart city transportation solutions
Implement multi-layer communication strategies
Comprehensive robotics course focusing on Robot Operating System (ROS) and Simultaneous Localization and Mapping (SLAM) technologies using Raspberry Pi as the primary computational platform.
ROS Installation and Setup
Raspberry Pi OS preparation
ROS Noetic/ROS2 installation
Development environment configuration
Cross-compilation techniques
ROS Core Concepts
Nodes and communication
Topics, services, and actions
Message passing
Package management
Launch file creation
Practical Networking
Master-slave configuration
Distributed computing
Network configuration
Multi-machine ROS setup
Creating custom ROS packages
Implementing basic publisher/subscriber nodes
Writing service and action servers
Message type definition
SLAM Algorithms
Gmapping
Cartographer
RTAB-Map
Hector SLAM
Visual SLAM approaches
Sensor Integration
LiDAR configuration
Depth camera setup
IMU sensor fusion
Odometry estimation
Mapping Strategies
2D and 3D mapping techniques
Loop closure mechanisms
Map optimization
Feature extraction and matching
Creating 2D occupancy grid maps
3D environment reconstruction
Real-time mapping demonstrations
Sensor calibration techniques
Movement Planning
Global and local planners
Cost map generation
Obstacle detection
Trajectory optimization
Navigation Algorithms
A* algorithm
Dijkstra's algorithm
RRT (Rapidly-exploring Random Tree)
Dynamic window approach
Autonomous Navigation
Waypoint navigation
Obstacle avoidance
Dynamic path recalculation
Multi-robot coordination
Sensor Integration Techniques
Kalman Filter fundamentals
Extended Kalman Filter (EKF)
Particle Filter
Sensor data alignment and synchronization
2. Multi-Sensor Fusion Architectures
IMU and GPS integration
LiDAR and camera fusion
Proprioceptive and exteroceptive sensor combination
Uncertainty modeling and management