Computer Vision for Autonomous Systems and Robotics Course

Training Outlines

Introduction

This professional course, "Computer Vision for Autonomous Systems and Robotics," is designed to equip participants with the skills necessary to understand and implement computer vision technologies within autonomous systems and robotic platforms. The course covers foundational concepts, practical implementation techniques, and the latest advancements in the field, providing hands-on experience alongside theoretical knowledge.

Objectives

• Understand the fundamental principles of computer vision.
• Explore the integration of computer vision in autonomous systems.
• Gain proficiency in practical tools and libraries used in computer vision.
• Analyze real-world applications and case studies for robotics.
• Develop skills to design and implement computer vision solutions for robotics.

Course Outlines

Day 1: Introduction to Computer Vision

• Overview of computer vision and its history.
• Key concepts and terminologies.
• Image processing techniques and tools.
• Introduction to OpenCV and other libraries.
• Setting up the development environment.

Day 2: Core Concepts in Computer Vision

• Understanding image formation and representation.
• Feature detection and matching.
• Edge detection and segmentation.
• Object recognition and classification.
• Hands-on exercises with sample datasets.

Day 3: Computer Vision for Autonomous Systems

• Integration of sensors and vision systems.
• 3D vision and depth perception.
• Stereo vision and depth reconstruction.
• Real-time image processing challenges.
• Case studies on autonomous vehicles and drones.

Day 4: Robotics and Vision-Based Control

• Introduction to robotics and vision integration.
• Vision-based navigation systems.
• Obstacle detection and avoidance.
• Visual Servoing and robotic manipulation.
• Practical implementations in robotic platforms.

Day 5: Advanced Topics and Future Trends

• Deep learning applications in computer vision.
• State-of-the-art algorithms and approaches.
• Exploration of SLAM and visual odometry.
• Future trends and research directions.
• Final project and presentations.

Training Schedule

Below is the table of cities along with the respective dates for the upcoming training sessions of Computer Vision for Autonomous Systems and Robotics Course. Please review the schedule to find the most convenient option for you. You can also use the below search bar to type the city name and filter the results.