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Duration 21 hours
Course Outline
Introduction to Computer Vision for Robotics
- Exploring computer vision applications within robotics.
- Addressing key challenges in perception and visual understanding.
- Configuring the development environment with OpenCV and Python.
Image Processing Fundamentals
- 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 with OpenCV
- Detecting objects using classical approaches (Haar cascades, HOG).
- Tracking moving objects within video streams.
- Incorporating visual feedback into robotic systems.
Deep Learning for Visual Perception
- Overview of convolutional neural networks (CNNs).
- Processes for training and deploying object detection models.
- Utilizing pre-trained models (YOLO, SSD, Faster R-CNN).
Sensor Fusion and Depth Perception
- Fusing camera data with LiDAR and ultrasonic sensors.
- Estimating depth and performing 3D reconstruction.
- Enabling perception for obstacle avoidance and navigation.
Vision-Based Control and Decision Making
- Applying computer vision to robotic manipulation tasks.
- Implementing visual servoing and closed-loop control.
- Enabling autonomous decision-making driven by visual input.
Deploying and Optimizing Vision Models
- Deploying models on embedded systems and edge devices.
- Optimizing inference performance for real-time scenarios.
- Troubleshooting issues and enhancing accuracy.
Summary and Next Steps
Requirements
- A solid grasp of fundamental robotics concepts.
- Proficiency in Python programming.
- Basic knowledge of machine learning principles.
Target Audience
- Robotics engineers.
- Computer vision practitioners.
- 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.
