ME-5524: Bayesian Robotics
Description: Principles of autonomous robotics control for unstructured environments. Probability theory, numerical techniques for recursive Bayesian estimation and multi-sensor data fusion, simultaneous localization and mapping, quantification of belief, Bayesian control. Prerequisite: Graduate Standing required.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 9
Average GPA: 3.89 (A)
Strict A Rate (No A-) : 74.12%
Average Withdrawal Rate: 0.00%
| Tomonari Furukawa | 2018 | 93.0% | 6.5% | 0.5% | 0.0% | 0.0% | 0.0% | 3.88 | 8 |
| Erik Komendera | 2023 | 94.4% | 5.6% | 0.0% | 0.0% | 0.0% | 0.0% | 3.96 | 1 |