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: 2
Average GPA: 3.97 (rounds to A)
Strict A Rate (No A-) : 93.65%
Average Withdrawal Rate: 0.00%
| Erik Komendera | 2024 | 97.2% | 2.8% | 0.0% | 0.0% | 0.0% | 0.0% | 3.97 | 2 |