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
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.
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.
Interesting material, the last programming assignment was very challenging. Lots of topics covered, a good introduction.
About the Robotics Specialization

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