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Course Outline
Introduction to Computer Vision in Robotics
- Survey of computer vision applications within robotics
- Core challenges in perception and visual interpretation
- Configuring the development environment with OpenCV and Python
Foundations of Image Processing
- Image representation and manipulation techniques
- Filtering, edge detection, and feature extraction methods
- Color space conversion and segmentation strategies
Object Detection and Tracking via OpenCV
- Object identification using traditional methods (Haar cascades, HOG)
- Tracking dynamic objects in video streams
- Incorporating visual feedback loops into robotic systems
Deep Learning for Visual Perception
- Introduction to convolutional neural networks (CNNs)
- Training and deploying object detection models
- Utilizing pre-trained architectures (YOLO, SSD, Faster R-CNN)
Sensor Fusion and Depth Perception
- Combining camera data with LiDAR and ultrasonic sensor inputs
- Depth estimation and 3D reconstruction processes
- Perceptual systems for obstacle avoidance and navigation
Vision-Driven Control and Decision Making
- Applying computer vision to robotic manipulation tasks
- Visual servoing and closed-loop control mechanisms
- Autonomous decision-making based on visual inputs
Deployment and Optimization of Vision Models
- Deploying models on embedded systems and edge devices
- Optimizing inference performance for real-time scenarios
- Debugging and enhancing model accuracy
Conclusion and Further Learning Paths
Requirements
- Fundamental knowledge of robotics concepts
- Proficiency in Python programming
- Basic understanding of machine learning principles
Target Audience
- Robotics engineers
- Computer vision practitioners
- Machine learning engineers
21 Hours
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.
