Course Outline
Introduction to Computer Vision for Robotics
- Exploring key applications of computer vision in robotics.
- Addressing critical challenges in perception and visual understanding.
- Establishing a development environment using OpenCV and Python.
Foundations of Image Processing
- Techniques for image representation and manipulation.
- Methods for filtering, edge detection, and feature extraction.
- Working with color spaces and segmentation techniques.
Object Detection and Tracking using OpenCV
- Identifying objects via classical methods such as Haar cascades and HOG.
- Tracking moving objects within video streams.
- Incorporating visual feedback loops into robotic systems.
Deep Learning for Visual Perception
- An introduction to convolutional neural networks (CNNs).
- Strategies for training and deploying object detection models.
- Utilizing pre-trained architectures like YOLO, SSD, and Faster R-CNN.
Sensor Fusion and Depth Perception
- Combining camera data with LiDAR and ultrasonic sensors.
- Estimating depth and performing 3D reconstruction.
- Enhancing obstacle avoidance and navigation through perception.
Vision-Based Control and Decision-Making
- Applying computer vision to robotic manipulation tasks.
- Implementing visual servoing and closed-loop control mechanisms.
- Enabling autonomous decision-making driven by visual input.
Deployment and Optimization of Vision Models
- Running models on embedded systems and edge devices.
- Optimizing inference performance for real-time responsiveness.
- Diagnosing issues and refining model accuracy.
Summary and Future Directions
Requirements
- A solid grasp of fundamental robotics concepts.
- Proficiency in Python programming.
- A basic understanding of machine learning principles.
Target Audience
- Robotics engineers.
- Computer vision specialists.
- Machine learning engineers.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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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.
