Probabilistic Inference, Belief Space Planning, Information Theoretic Costs, Belief Space Planning Approaches For Autonomous Navigation And Active Slam, Gaussian Processes, Relation Between Belief Space Planning and Reinforcement Learning. Learning Outcomes The Student Will Acquire Fundamental Understanding of The Mathematical Models and Solution Methods For Planning Under Uncertainty (belief Space Planning) in The Context of Mobile Robotics and in Particular, Autonomous Navigation and Perception.

Faculty: Aerospace Engineering
|Undergraduate Studies |Graduate Studies

Pre-required courses

44202 - Random Signals or 86733 - Random Processes in Aerospace Systems or 234247 - Algorithms 1


Course with no extra credit (contains)

97252 - Autonomous Planning Under Uncertainty


Semestrial Information