Introduction
Here you find the accompanying paper and the slides we used for a talk about robotics in the context of artificial intelligence. Read the abstract below for more info. It was held in the context of the proseminar "Artificial Intelligence" at the RWTH Aachen in summer semester 2003.I have also put all links mentioned in the document here and links to some of the other documents that are available as digital documents on the web.
This is a first try for such a paper so read carefully and read the referenced material for a real understanding. This is more a summary of some basic parts of robotics. It may be useful for some other students who work on similar introductions.
If you plan to have an introductory report about robotics consider to read "Artificial Intelligence - A Modern Approach, Second Edition" either. This is a pretty good start. If you want to get into more detail about Monte Carlo Localization you should dig into the document mentioned below. It is very detailed. We did not have enough time for in-depth information so it is not really covered in this talk. The latter references below are meant for interested beginners for some practical views like Mindstorm bots. They may be interesting for geeks who have some fun on creating such an introductory talk.
For other accompanying papers about other topics in artificial intelligence are available here (most are written in German).
Abstract
This document gives a short introduction to the basics of robotics in the context of artificial intelligence. It describes the very basics of robotics like sensors and effectors, gives an overview on robotic history, and introduces some basic problems encountered in modern robotics. It describes possible solutions to those problems without going deeply into theory. The problems introduced are perception, basic pose description, transition and sensor models, localization as a special case of perception (Monte Carlo Localization, Extended Kalman Filter), representation of environment (workspace and configuration space), path planning (cell decomposition, potential fields, skeletonization, Voronoi diagrams, and probabilistic roadmaps), movement of robots, and some real-life examples.This document was created accompanying a talk in the context of the proseminar "Artificial Intelligence" in summer semester 2003 at the RWTH Aachen.
Authors
The authors of this accompanying paper are Sumedha Widyadharma and Tim Niemueller. We were assisted by Günther Gans from the Knowledge-based Systems Group at Computer Science V, RWTH Aachen.References
- Artificial Intelligence - A Modern Approach (AIMA), Second Edition (2003), Stuart Russel and Peter Norvig
- Artificial Intelligence - A Modern Approach (AIMA), First Edition (1995), Stuart Russel and Peter Norvig
- Monte Carlo Localization for Mobile Robots, F. Dellaert, D. Fox, W. Burgard and S. Thrun
- Robotic Mapping: A Survey, Sebastian Thrun
- An Introduction to the Kalman Filter, Greg Welch and Gary Bishop
- Trimble - What is GPS?, Trimble Navigation Limited
- IndiGolog Overview, G. De Giacomo, Y. Lesperance, H. Levesque and R. Reiter
- Voronoi Diagram, Eric W. Weisstein
- Small Robot Sensors, Bob Grabowski
- Minibot Sonar Sensor Howto, Kam Leang
- Moving Eye - Virtual Laboratory Excercise on Telepresence, Augmented Reality, and Ball-Shaped Robotics, Helsinki University of Technology
- Robocup
- Robocup 2003
- AllemaniACs Robocup Team RWTH Aachen
- Synchro drive robot platform, Doug Carlson
- Lego Mindstorms Tutorial on correcting course, Lego
- Star Trek TNG Episode: The Measure Of A Man
Used tools
Download
This document is released and distributed under the terms of the GNU Free Documentation License (GFDL).By downloading and/or using this document you agree to this license!
| Accompanying paper | PostScript gzipped (408713 Bytes) | Portable Document Format (1361677 Bytes) | ||
| Slides | PostScript gzipped (374534 Bytes) | Portable Document Format (1312499 Bytes) |
