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
- Exploring the role of computer vision in robotic applications
- Addressing key challenges in perception and visual understanding
- Establishing a development environment with OpenCV and Python
Core Image Processing Concepts
- Managing image representation and manipulation
- Applying filtering, edge detection, and feature extraction
- Utilizing color spaces and segmentation techniques
Object Detection and Tracking via OpenCV
- Identifying objects using classical methods (Haar cascades, HOG)
- Tracking moving objects within video streams
- Incorporating visual feedback into robotic systems
Deep Learning for Enhanced Visual Perception
- Understanding convolutional neural networks (CNNs)
- Training and implementing object detection models
- Leveraging pre-trained models (YOLO, SSD, Faster R-CNN)
Sensor Fusion and Depth Perception
- Combining camera data with LiDAR and ultrasonic sensors
- Performing depth estimation and 3D reconstruction
- Enabling obstacle avoidance and navigation through perception
Vision-Driven Control and Decision-Making
- Applying computer vision to robotic manipulation tasks
- Implementing visual servoing and closed-loop control
- Facilitating autonomous decision-making based on visual inputs
Deployment and Optimization of Vision Models
- Implementing models on embedded systems and edge devices
- Enhancing inference performance for real-time scenarios
- Debugging and refining accuracy
Concluding Remarks and Future Directions
Requirements
- A solid grasp of fundamental robotics concepts
- Proficiency in Python programming
- A 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.