How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves. You will come to understand how grasping objects is facilitated by the computation of 3D posing of objects and navigation can be accomplished by visual odometry and landmark-based localization.
This course is part of the Robotics Specialization
About this Course
Skills you will gain
- Computer Vision
- Random Sample Consensus (Ransac)
Syllabus - What you will learn from this course
Geometry of Image Formation
- 5 stars59.96%
- 4 stars24.96%
- 3 stars7.53%
- 2 stars4.08%
- 1 star3.45%
TOP REVIEWS FROM ROBOTICS: PERCEPTION
Great course for those who wants to understand how classical SLAM systems work. I think it would be a bit more practical if the assignments were made in python.
This is quite challenging course. So far, this is the course with the largest amount of material, I wish the class will be split into two courses.
The concepts were explained very well and clearly. The last week content seemed a bit complicated to follow, but it was not unsolvable. I enjoyed the course. Thank you!
The content is not very easy to understand because the lecture speaks very fast and the document is not very sufficient. But in all, the content is good, help me with my research.
About the Robotics Specialization
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