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
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About this Course
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Try Coursera for BusinessSkills you will gain
- Computer Vision
- Estimation
- Random Sample Consensus (Ransac)
- Geometry
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Syllabus - What you will learn from this course
Geometry of Image Formation
Projective Transformations
Pose Estimation
Multi-View Geometry
Reviews
- 5 stars59.96%
- 4 stars24.96%
- 3 stars7.53%
- 2 stars4.08%
- 1 star3.45%
TOP REVIEWS FROM ROBOTICS: PERCEPTION
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.
One of the most usefful courses I have taken by the coursera. Thank you for useful materail covered here.
Outstanding Course! I could always count on Prof.Jianbo to crunch some of the most complex and confusing parts of the course into a much easier understandable language.
The 4th week content is hard to follow than the previous three. It would be better if more detailed math and examples are provided in the 4th week.
About the Robotics Specialization

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