Visual Navigation and Foundation Models for Autonomy

Catalog description

Credits 3. 2 Lecture Hours. 2 Lab Hours. Introduction to the principles and modern techniques of visual navigation and autonomy for robotic systems beginning with geometric foundations and numerical methods; fundamental concepts in visual perception and localization as applied to robotic system navigation; fundamental techniques in motion planning for robotic systems; applications of model machine learning techniques to different modules in the autonomous navigation pipeline. Prerequisites: Graduate classification.