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Duration 21 hours
Course Outline
Foundations of Computer Vision in Robotics
- Exploring the role of computer vision in robotic applications
- Addressing key challenges in visual perception and understanding
- Configuring the development environment with OpenCV and Python
Core Principles of Image Processing
- Understanding image representation and manipulation techniques
- Applying filtering, edge detection, and feature extraction methods
- Working with color spaces and segmentation algorithms
Object Detection and Tracking via OpenCV
- Identifying objects using traditional techniques (Haar cascades, HOG)
- Tracking dynamic objects within video streams
- Incorporating visual feedback mechanisms into robotic systems
Deep Learning for Enhanced Visual Perception
- Introduction to Convolutional Neural Networks (CNNs)
- Training and deploying specialized object detection models
- Utilizing state-of-the-art pre-trained models (YOLO, SSD, Faster R-CNN)
Sensor Fusion and 3D Depth Perception
- Combining camera data with LiDAR and ultrasonic sensor inputs
- Techniques for depth estimation and 3D scene reconstruction
- Implementing perception systems for obstacle avoidance and navigation
Vision-Driven Control and Decision-Making
- Applying computer vision to robotic manipulation tasks
- Implementing visual servoing and closed-loop control strategies
- Enabling autonomous decision-making processes based on visual inputs
Deployment and Optimization of Vision Models
- Deploying models on embedded systems and edge devices
- Enhancing inference performance for real-time operational needs
- Debugging and refining system accuracy
Conclusion and Future Directions
Requirements
- Solid grasp of fundamental robotics principles
- Proficiency in Python programming
- Working knowledge of core machine learning concepts
Target Audience
- Robotics Engineers
- Computer Vision Specialists
- Machine Learning Engineers
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
