Welcome!

Welcome to the 2007 Player Summer School on Cognitive Robotics!

The first edition of the PSSCR is co-organized by the Intelligent Autonomous Systems research group at the Technische Universität München, Germany and the Artificial Intelligence Center at SRI, International, USA. The venue will take place during 13-20 August 2007, in Munich, Germany.

The event is sponsored by the Cognition for Technical Systems (CoTeSys) excellence cluster at TUM, and the European Robotics Research Network (EURON).

Registered users can click here to login.

Summer School Material

The Program section just got updated with a few videos and presentations from the lecturers. We are working on getting the rest available online for download.

PS. Our apologies for the sound problems in some of the videos.

Pictures from the summer school lectures and practicals

The first bits from the summer school lectures and practicals are available at http://psscr07.cs.tum.edu/image . Let us know if you have any problems opening or downloading them.

Summer school content (slides, presentations, etc)

We are currently working on making the presentations (both lectures and invited talks) from the summer school available. Things are a bit slow these days because most of our staff took some free days off so most of us are traveling at the moment. However, we will try to get everything online as soon as possible. Thanks for understanding.

Pictures from the Summer School

Many participants agreed it would be a good idea to upload a selection of the pictures taken by us during PSSCR'07
We managed it at the hotel the last day after the lectures.

http://ogai.org/events/PSSCR07/index.html

EOS: End Of School

The summer school has ended. Thanks to everyone who participated.

Robot Learning Pointers

Recommended textbooks for robot learning
========================================

Bishop, "Pattern Recognition and Machine Learning"
http://research.microsoft.com/~cmbishop/PRML/

Bishop, "Neural Networks for Pattern Recognition"
http://research.microsoft.com/~cmbishop/nnpr.htm

Duda, Hart, and Stork, "Pattern Classification"
http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471056693.html

MacKay, "Information Theory, Inference, and Learning Algorithms"
http://www.inference.phy.cam.ac.uk/mackay/itila/

(I especially recommend Chapter 45 for an introduction to Gaussian Processes: http://www.inference.phy.cam.ac.uk/mackay/itprnn/ps/534.548.pdf My Matlab implementation of Gaussian Process regression was implemented from this chapter without too much difficulty.

Thrun, Burgard, and Fox "Probabilistic Robotics"
http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10668

Russell and Norvig, "Artificial Intelligence: A Modern Approach"
http://aima.cs.berkeley.edu/

Sampling of related conferences to machine and robot learning
=============================================================

Machine Learning
NIPS - http://nips.cc/
ICML - http://icml2008.cs.helsinki.fi/

Computational Learning Theory
COLT - http://colt2008.cs.helsinki.fi/

Data Mining
KDD - http://www.acm.org/sigs/sigkdd/kdd2008/

Developmental Robotics
ICDL - http://www.icdl07.org/
EpiRob - http://www.epigenetic-robotics.org/

General Robotics
ICRA - http://www.icra2008.org/
R:SS - http://roboticsconference.org/

Human-Robot Interaction
HRI - http://hri2008.org/

Artificial Life
ALife - http://www.alifex.org/

Lab 5 files

Files for lab5.

Data Files:
training.dat - Use this to train your KNN
test.data - Test your knn with this

Writing you KNN classifier:
*Fill in the first function in ncc_skel.cc
*Compile, and run ./skel to test.
*Use gnuplot to visualize your output:
**gnuplot> plot 'test_classified_1.data' , 'test_classified_2.data'

Logging Data:
*player datacapture.cfg
*./datacapture
*Once the client program is running, move the robot or targets around to desired location. *Press any alpha key (a-z) + Enter to log laser data. Answer the questions that follow.

Classifying Data:

Lab 4 files

Files for lab 4

To open the .tar file:

$ tar cvf lab4
$ cd lab4
$ make

The file carlikeclient.cc has an example of commanding with desired speed and heading.

Kurt's slides are at:
http://www.ai.sri.com/~konolige/cs225b/slides/05-sensor_interpretation.p...

Lab 2 files

Files necessary for lab 2.

To unpack the .tar file:

$ tar xvf lab2.tar
$ cd lab2

To run player:

$ player pss.cfg

To compile:

$ make -f Makefile.txt

(or rename Makefile.txt to Makefile, then just type 'make')

Syndicate content

Navigation