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Duration 21 hours
Course Outline
Introduction to Robotics Computer Vision
- Exploring the scope of computer vision applications in robotics
- Identifying critical challenges in perception and visual understanding
- Configuring the development environment with OpenCV and Python
Core Image Processing Concepts
- Methods for image representation and manipulation
- Techniques for filtering, edge detection, and feature extraction
- Understanding color spaces and segmentation strategies
Object Detection and Tracking via 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)
- Training and deploying advanced object detection models
- Utilizing pre-trained architectures (YOLO, SSD, Faster R-CNN)
Sensor Fusion and Depth Perception
- Integrating camera data with LiDAR and ultrasonic sensors
- Estimating depth and performing 3D reconstruction
- Enhancing 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
Deployment and Optimization of Vision Models
- Deploying models on embedded systems and edge devices
- Optimizing inference performance for real-time operational requirements
- Diagnosing issues and improving model accuracy
Conclusion and Future Directions
Requirements
- Foundational understanding of core robotics principles
- Proficiency in Python programming
- Working knowledge of machine learning fundamentals
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.
