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Course Outline
Foundations of Computer Vision in Robotics
- Examining the role of computer vision in modern robotic applications
- Addressing critical challenges in visual perception and understanding
- Configuring a development environment using OpenCV and Python
Core Image Processing Techniques
- Methods for image representation and manipulation
- Applying filters, detecting edges, and extracting key features
- Utilizing color spaces and advanced 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
- Feeding visual feedback directly into robotic control systems
Deep Learning for Enhanced Visual Perception
- Understanding the architecture of convolutional neural networks (CNNs)
- Processes for training and deploying object detection models
- Leveraging pre-trained architectures like YOLO, SSD, and Faster R-CNN
Sensor Fusion and Depth Analysis
- Combining camera inputs with LiDAR and ultrasonic sensor data
- Performing depth estimation and 3D scene reconstruction
- Enabling obstacle avoidance and navigation through enhanced perception
Visual Control and Autonomous Decision-Making
- Applying computer vision to precise robotic manipulation tasks
- Implementing visual servoing and closed-loop control mechanisms
- Driving autonomous decisions based on real-time visual data
Model Deployment and Performance Optimization
- Implementing vision models on embedded systems and edge devices
- Refining inference speeds for real-time operational requirements
- Diagnosing issues and enhancing model accuracy
Conclusion and Future Directions
Requirements
- A solid grasp of fundamental robotics principles
- Proficiency in Python programming
- Foundational knowledge of machine learning concepts
Target Audience
- Robotics Engineers
- Computer Vision Specialists
- 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.
