3.0

credits

Average Course Rating

The goal of this course is to explore machine learning and perception algorithms focused on robotic applications. Topics will include robot localization and mapping, pedestrian/obstacle detection/prediction, semantic segmentation, perception-based grasp planning, continual learning for perception algorithms and multimodal sensor fusion. This course will include introductions to the topics by the instructor followed by paper reading and discussions led by the students. In addition, this course will consist of an in-depth semester long project that will emphasize research skills including developing a hypothesis, conducting literature reviews, formulating the problem, defining, and conducting experiments and finally evaluating and reporting results. Required Course Background: Programming, Linear Algebra, Prob/Stat, Computer Vision and (Machine Learning or ML: Deep Learning).