Final Project Demonstration
Course Description
This course is intended for students advancing in the study of robotic engineering. The focus is on the problems of how a robot can learn to perceive the physical world well enough to act in it and make reliable plans. Subjects covered by this course include robotic collaboration, kinematics, robotic vision, calibration, RGB-D sensing, object recognition, artificial intelligence (AI), and deep learning (DL). Specific projects will be carried out throughout this course regarding the simulation of robot picking using fundamental kinematics and robot vision, an AI robot to play tic-tac-toe game, and a DL robot to play arcade claw game.
- e teach students how to conduct the basic kinematic formulation of a robotic system in simulation.
- To teach students how to use robotic vision, including algorithms, hardware, and software, in simulation.
- To teach students how to program artificial intelligence into robot hardware performing interactive tasks.
- To teach students how to use deep learning methods to program robot hardware to perform advanced tasks.
- To reinforce students’ team skills through various team projects, including problem formulation, problem solutions, and written reporting of results.
- To reinforce students’ visualization and hands-on skills through project virtual prototyping and/or physical construction exercises.
Related information regarding this course:
- This course was also offered in Spring, 2019 and Spring, 2020.
- The Machine Intelligence Design and Learning Lab.
- ME336 Robotics & AI Guest Lecture Series.
Course Instructors & Teaching Support
Course Schedule
Class Time & Location
- Room 235
- New Engineering Building
Grading Policy
- Assignment Project #1: 30%
- Assignment Project #2: 30%
- Course Project: 30%
- Individual Marking: 10%
Pre-requisites
- MEE5101 Introduction to Robotics and Automation
- MEE5104 Robotic Modeling and Control
Robotics & AI Guest Lecture Series
Team Formulation
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Lecture & Lab Notes
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| Week # | Wednesday 1400~1550 | Friday 0800~0950 |
|---|---|---|
| 1 | 01-13-2021 L01-Course Introduction | 01-15-2021 L02-CoBot Designs |
| 2 | 01-20-2021 P01-Project Overview G01-He Weipeng | 01-22-2021 L03-Robot Perception |
| 3 | 03-03-2021 L04-Machine Learning I | 03-05-2021 P02-DeepClaw Tutorial |
| 4 | 03-10-2021 L05-Machine Learning II | 03-12-2021 P03-Hand-eye Calibration |
| 5 | 03-17-2021 L06-Deep Networks I | 03-19-2021 P04-Assignment Project 1 |
| 6 | 03-24-2021 L07-Deep Networks II | 03-26-2021 P05-Assignment Project 1 |
| 7 | 03-31-2021 L08-Network Tuning I | 04-02-2021 P06-Data Collection |
| 8 | 04-07-2021 L09-Network Tuning II | 04-09-2021 P07-Assignment Project 2 |
| 9 | 04-14-2021 L10-Markovian Models I | 04-16-2021 P08-Assignment Project 2 |
| 10 | 04-21-2021 L11-Markovian Models II | 04-23-2021 P09-Project 3 Review |
| 11 | 04-28-2021 L12-Reinforcement Learning | 04-30-2021 P10-Assignment Project 3 |
| 12 | 05-05-2021 No Class | 05-07-2021 P11-Assignment Project 3 |
| 13 | 05-12-2021 G03-Wang Tao | 05-14-2021 P12-Assignment Project 3 |
| 14 | 05-19-2021 G02-Wang Guangneng | 05-21-2021 P13-Assignment Project 3 |
| 15 | 05-26-2021 P14-Final Report | 05-28-2021 P15-Final Presentation |