Advanced Estimation Methods for Autonomous Robotic Systems
The participants learn to independently explore and understand a given topic and present it to the other participants in a concise and coherent way.
| Intended Participants | Master students |
| Instructors | Benjamin Noack |
| SWS | 2 |
| Credits | 6 |
| Languages | English / German |
| Recommended Prerequisites | Attendance of Lecture AMR is helpful |
| Kick-Off |
Thursday, 17:00 - 18:30, |
Course Description
For an autonomous robotic system, being able to extract information, e.g., about its position, orientation, and its surroundings, from sensor readings, is essential for its successful and safe operation.
This seminar covers a variety of methods, such as nonlinear versions of the Kalman filter, particle filters, moving horizon estimation, as well as Bayesian estimation for discrete-valued quantities, for such robotic estimation tasks.
Registration
Please enroll to the elearning waitlist. After the kickoff meeting, the elearning course will be opened.
For any additional questions regarding the project or for any issues with registration, please email