How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.
About this Course
Skills you will gain
- 5 stars58.50%
- 4 stars20.85%
- 3 stars12.34%
- 2 stars4.04%
- 1 star4.25%
TOP REVIEWS FROM ROBOTICS: ESTIMATION AND LEARNING
Course content needs researching on the internet as well. And course assignments are good learning experience but need research too.
The material is clearly presented. The Matlab exercises complement and reinforce the subject, the level of difficulty is well balanced, thanks for this great course.
It's a great course. Although the assignment is little tough, you will gain a lot after completing it.
Excellent exposure to mapping, localization, etc. Would have liked to have odometry included in the week4 assignment.
About the Robotics Specialization
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