Enroll Course: https://www.coursera.org/learn/robotics-perception
Robots are becoming increasingly sophisticated, capable of navigating complex environments and performing intricate manipulation tasks. But how do they truly ‘see’ and understand the world around them? Coursera’s ‘Robotics: Perception’ course dives deep into this fascinating question, equipping learners with the foundational knowledge of how robots process visual information.
This course, part of a larger robotics specialization, focuses specifically on the perception aspect. It starts with the fundamental ‘Geometry of Image Formation,’ explaining the mathematical models that govern how cameras capture light and project 3D scenes onto 2D images. Understanding this geometric relationship is crucial for any aspiring roboticist, as it lays the groundwork for interpreting visual data.
The syllabus then progresses to ‘Projective Transformations.’ This module tackles the inherent challenges of losing a dimension during image projection. Concepts like vanishing points are introduced, providing insights into how we can infer 3D information from 2D representations, a key skill for robots navigating real-world spaces.
A significant portion of the course is dedicated to ‘Pose Estimation.’ Here, you’ll learn practical techniques for feature extraction and tracking across image sequences. The course covers how to identify salient points in an image and follow them through video, enabling robots to understand their position relative to their surroundings using methods like Homographies, and how to handle noisy data with techniques like least squares and RANSAC.
Finally, ‘Multi-View Geometry’ extends these concepts to video sequences. You’ll explore crucial geometric constraints like the Epipolar constraint, which helps in understanding the relative motion between camera frames. The course culminates in ‘Structure from Motion,’ where you’ll learn to reconstruct a robot’s trajectory and build a 3D map of its environment. This module often involves advanced techniques like Bundle Adjustment for refining estimates.
**Recommendation:**
‘Robotics: Perception’ is an excellent course for anyone interested in the visual intelligence of robots. Whether you’re a student, a hobbyist, or a professional looking to expand your skills, this course offers a rigorous yet accessible introduction to computer vision techniques essential for robotics. The blend of theory and practical applications makes it highly valuable. While it can be mathematically intensive at times, the clear explanations and structured approach make it manageable. If you want to understand how robots perceive their environment, this course is a must-take.
Enroll Course: https://www.coursera.org/learn/robotics-perception