Spring 2023 Mechanical Engineering E6616 section 001


Call Number 15379
Day & Time
TR 1:10pm-2:25pm
428 Pupin Laboratories
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 85 students (150 max) as of 8:44PM Wednesday, February 28, 2024
Subject Mechanical Engineering
Number E6616
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20231MECE6616E001