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Duration 21 hours
Course Outline
Introduction to Computer Vision in Robotics
- Examining the role of computer vision in modern robotics.
- Identifying key challenges in perception and visual understanding.
- Configuring the development environment with OpenCV and Python.
Foundations of Image Processing
- Techniques for image representation and manipulation.
- Mastery of filtering, edge detection, and feature extraction.
- Exploring color spaces and segmentation methodologies.
Object Detection and Tracking via OpenCV
- Utilizing classical methods such as Haar cascades and HOG for object detection.
- 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.
- Application of pre-trained architectures like YOLO, SSD, and Faster R-CNN.
Sensor Fusion and Depth Perception
- Synthesizing camera data with LiDAR and ultrasonic sensor inputs.
- Methods for depth estimation and 3D reconstruction.
- Enhancing obstacle avoidance and navigation through perception.
Vision-Based Control and Decision Making
- Applying computer vision techniques to robotic manipulation tasks.
- Implementing visual servoing and closed-loop control systems.
- Developing autonomous decision-making strategies based on visual inputs.
Deployment and Optimization of Vision Models
- Strategies for deploying models on embedded systems and edge devices.
- Optimizing inference speed for real-time application performance.
- Techniques for troubleshooting and enhancing model accuracy.
Summary and Next Steps
Requirements
- Foundational understanding of core robotics concepts.
- Proficiency in Python programming.
- Working knowledge of machine learning fundamentals.
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.
