Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 21 hours
Course Outline
Introduction to Computer Vision in Robotics
- Exploring the role of computer vision in robotic applications
- Addressing key challenges in perception and visual interpretation
- Configuring a development environment with OpenCV and Python
Foundations of Image Processing
- Understanding image representation and manipulation techniques
- Techniques for filtering, edge detection, and feature extraction
- Working with color spaces and segmentation methods
Object Detection and Tracking via OpenCV
- Identifying objects using traditional approaches such as Haar cascades and HOG
- Tracking dynamic objects within video streams
- Incorporating 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
- Utilizing pre-trained architectures like YOLO, SSD, and Faster R-CNN
Sensor Fusion and Depth Awareness
- Merging camera feeds with data from LiDAR and ultrasonic sensors
- Estimating depth and performing 3D reconstruction
- Enabling obstacle avoidance and navigation through perception
Vision-Driven Control and Decision Making
- Applying computer vision techniques to robotic manipulation
- Implementing visual servoing and closed-loop control strategies
- Making autonomous decisions based on visual inputs
Deployment and Model Optimization
- Running models on embedded systems and edge devices
- Enhancing inference speed for real-time operational needs
- Debugging issues and refining model accuracy
Conclusion and Future Directions
Requirements
- A foundational grasp of basic robotics principles
- Proficiency in Python programming
- Basic knowledge of machine learning concepts
Target Audience
- Robotics engineers
- Computer vision professionals
- 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.
