- Instructor: Prof.
Sung-Hyuk Cha
- CRN: 99729
- Meeting:
- Meeting Times: MW 01:25 - 3:25 PM, Fall 2005
- Place: PLV Goldstein rm 320
- Description:
This is a project-based course using pyro (Python Robotics). This course
addresses the problems of controlling and motivating robots to act
intelligently in dynamic, unpredictable environments. Major topics will
include: navigation and control, mapping and localization, robot
perception using vision and sonar, kinematics and inverse kinematics, and
robot simulation environments. To demonstrate these concepts we will be
using a simulated robot (and lego if possible).
The goal of this course is to introduce students to the primary
approaches to Robotics and Artificial Intelligence, including computer vision, game playing, genetic algorithms, neural network learning, self-organizaing map
statistical learning methods, and Bayesian learning.
It is intended to provide enough background to allow students to apply Robotics techniques to learning problems in a variety of application areas. Course projects will be required.
- Prerequisites: None
- Lecture Notes: can be accessed using the http://blackboard.pace.edu
Blackboard Login Procedures for Registered Students are available
here
- Useful Links: click here
- Project: click here.
- Tentative Schedule:
| Week |
Topic |
| 1 |
Introduction |
| 2 |
Python and Pyro |
| 3 |
Python and Pyro
|
| 4 |
Search
|
| 5 |
Game Playing |
| 6 |
Game Playing |
| 7 |
Artificial Neural Networks |
| 8 |
Artificial Neural Networks
|
| 9 |
Instance-Based Learning |
| 10 |
Genetic Algorithms |
| 11 |
Genetic Algorithms |
| 12 |
computer vision |
| 13 |
computer vision |
| 14 |
Self-organizing map |
| 15 |
Project presentation & Demo |
| |
|
- Evaluation:
- Project (50%): Students are required to implement
one Robotics application (Presentation and report required.)
- Report (20%): 10 page (double spaced) final report.
- Programming Assignment (30%): Python language programming
|