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.
- 5 stars58.53%
- 4 stars20.73%
- 3 stars12.39%
- 2 stars4.06%
- 1 star4.26%
来自ROBOTICS: ESTIMATION AND LEARNING的热门评论
Course content needs researching on the internet as well. And course assignments are good learning experience but need research too.
The course is too difficult and the class is too short to understand, I have to spend a lot of this learn the knowledge needed in other place.
Week 1 and Week 3 are organized much better than Week 2 and Week 4. If you don't have enough time, I recommend that you focus on Week 1 and 3.
Very succinct lectures which provides necessary foundation to learn advanced localization algorithms.