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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 ROBOT LEARNING | |
| Call Number | 13879 |
| Day & Time Location |
TR 1:10pm-2:25pm 501 Northwest Corner Building |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Matei T Ciocarlie |
| Type | LECTURE |
| 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 2:11PM Friday, May 20, 2022 |
| Subject | Mechanical Engineering |
| Number | E6616 |
| Section | 001 |
| Division | School of Engineering and Applied Science: Graduate |
| Open To | Engineering:Undergraduate, Engineering:Graduate, GSAS |
| Campus | Morningside |
| Section key | 20221MECE6616E001 |
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