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
Foundations of Computer Vision in Robotics
- Examining the role of computer vision applications within robotic systems
- Addressing the primary challenges associated with perception and visual interpretation
- Configuring the development workflow with OpenCV and Python
Core Image Processing Concepts
- Understanding image representation and manipulation techniques
- Applying filtering, edge detection, and feature extraction methods
- Utilizing color spaces and segmentation approaches
Object Detection and Tracking with OpenCV
- Identifying objects through classical methods such as Haar cascades and HOG
- Monitoring moving objects within continuous video streams
- Incorporating visual feedback mechanisms into robotic architectures
Deep Learning for Visual Perception
- Exploring the structure and function of convolutional neural networks (CNNs)
- Developing and deploying models for object detection
- Leveraging pre-trained architectures like YOLO, SSD, and Faster R-CNN
Sensor Fusion and Depth Perception
- Merging camera data with inputs from LiDAR and ultrasonic sensors
- Performing depth estimation and 3D reconstruction
- Facilitating obstacle avoidance and navigation through perception
Vision-Based Control and Decision Making
- Enhancing robotic manipulation capabilities using computer vision
- Implementing visual servoing and closed-loop control systems
- Enabling autonomous decision-making driven by visual input
Deployment and Optimization of Vision Models
- Running models on embedded systems and edge devices
- Refining inference performance for real-time operational needs
- Diagnosing issues and enhancing model accuracy
Conclusion and Future Directions
Requirements
- A solid grasp of fundamental 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.
