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Duration 21 hours
Course Outline
Introduction to Computer Vision in Robotics
- Exploring the role of computer vision in robotic applications
- Addressing key challenges in visual perception and understanding
- Establishing the development environment with OpenCV and Python
Foundations of Image Processing
- Image representation and manipulation techniques
- Filtering, edge detection, and feature extraction methods
- Working with colour spaces and segmentation strategies
Object Detection and Tracking using OpenCV
- Identifying objects through classical approaches (Haar cascades, HOG)
- Tracking moving objects within video streams
- Integrating visual feedback mechanisms into robotic systems
Deep Learning for Visual Perception
- An overview of convolutional neural networks (CNNs)
- Processes for training and deploying object detection models
- Utilising pre-trained architectures (YOLO, SSD, Faster R-CNN)
Sensor Fusion and Depth Perception
- Combining camera data with LiDAR and ultrasonic sensor inputs
- Techniques for depth estimation and 3D reconstruction
- Perception strategies 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 systems
- Enabling autonomous decision-making based on visual inputs
Deployment and Optimization of Vision Models
- Implementing models on embedded systems and edge devices
- Optimising inference performance for real-time responsiveness
- Strategies for troubleshooting and enhancing accuracy
Wrap-up and Future Directions
Requirements
- A solid grasp of fundamental robotics concepts
- Proficiency in Python programming
- Working knowledge of machine learning principles
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.
