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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.

Spring 2022 Mechanical Engineering E6616 section 001

Call Number 13879
Day & Time
TR 1:10pm-2:25pm
501 Northwest Corner Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Matei T Ciocarlie
Method of Instruction In-Person
Course Description Robots using machine learning to achieve high performance in unscripted situations. Dimensionality reduction, classification, and regression problems in robotics. Deep Learning: Convolutional Neural Networks for robot vision, Recurrent Neural Networks, and sensorimotor robot control using neural networks. Model Predictive Control using learned dynamics models for legged robots and manipulators. Reinforcement Learning in robotics: model-based and model-free methods, deep reinforcement learning, sensorimotor control using reinforcement learning.
Web Site Vergil
Department Mechanical Engineering
Enrollment 102 students (150 max) as of 8:03AM Monday, November 28, 2022
Subject Mechanical Engineering
Number E6616
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20221MECE6616E001

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SIS update 11/28/22 08:03    web update 11/28/22 08:24