## This is the information of year 2004.

• The information of previous year can be found here.
• The information of the current year can be found here.

## Description

The official description of course baiZSB6 can be found (in Dutch) here. The organisation part is already outdated. Also a Blackboard portal to this information is available.

### Contents

• Search Algorithms
Game playing is an example of type of problems that can easily decomposed in subproblems. For interesting games, like chess, the tree of subproblems grows to fast to be searched exhaustively, so other approaches are necessary. To solve the game we have to find a solution tree regardless of the opponent's replies. The natural way to represent such a two person, perfect information game, is with AND/OR graphs. Our positions are are represented as OR-nodes, because we have only to make one winning move. Their positions are represented as AND-nodes, because if their is winning move for the opponent, we have to assume that they will find it.
• Problem decomposition
• AND/OR graphs
• MiniMax principle
• alpha-beta algorithm

• Path planning
You have had planning algorithms such as A* that work on graphs. So let's try to reformulate the path planning problem as a graph problem. These graphs are somewhat special, it is convenient to see them as discretized spaces because this leads to better implementations. So then we need the notion of configuration space to explain the graph's properties.
• A* revisited
• Mapping path planning as graph search
• Task space and discretized configuration space
• Kinematics -> connectivity
• Criteria -> metric
• Obstacles -> forbidden nodes
• Examples: robot arm and self-parking car
• Other approaches of mapping path planning into graphs

• Trajectory planning
If you have setpoints, how to make it into a controllable path.

• Rigid body motion
• physical rigid bodies as idealization
• physical space as vector space
• representing motions using linear algebra (coordinate-free)
• isometries
• proof of decomposition theorem: rigid body motion = rotatio n followed by translation
• coordinates: vector spaces in the computer
• rotation matrices: how to design them
• reference angles: Euler angles
• homogeneous coordinates

• Denavit-Hartenberg notation
• Forward kinematics
• Inverse kinematics (briefly)
• Redundancy and degeneracy (briefly)
• Differential kinematics

## Schedule

Week 23

 date time type subject location lecturer/assistant Monday 31/5 Whit Monday Tuesday 1/6 10.00-10.15 L1 Course OverviewLecture (614 Kb) Studio Classroom - Amstel Instituut, Kruislaan 404 Arnoud Visser Tuesday 1/6 10.15-12.00 L1 Problem Decomposition and AND/OR Graphs Studio Classroom - Amstel Instituut, Kruislaan 404 Maarten van Someren Tuesday 1/6 12.30-14.30 W1 decomposition problems Studio Classroom - Amstel Instituut, Kruislaan 404 Maarten van Someren Tuesday 1/6 15.00-17.00 L2 the minimax principle and the alpha-beta algorithm Studio Classroom - Amstel Instituut, Kruislaan 404 Maarten van Someren Wednesday 2/6 10.00-12.30 P1 Checkmate P.126 Matthijs Spaan, Coen Pieterse Wednesday 2/6 13.00-15.00 L4 Qualitative NavigationLecture (461 Kb)Movie (88 MB) P.017 Arnoud Visser Wednesday 2/6 15.30-16.30 W2 introduction Dataconversion Studio Classroom - J.302 Valckenierstraat 65 Matthijs Spaan, Coen Pieterse Thursday 3/6 10.00-12.30 P1 Checkmate P.126 Matthijs Spaan, Coen Pieterse Thursday 3/6 13.00-15.00 L5 Quantative NavigationLecture (126 Kb) P.017 Arnoud Visser Friday 4/6 10.00-12.30 P2 A* in Java P.126 Matthijs Spaan, Coen Pieterse

Week 24

 date time type subject location lecturer/assistant Monday 7/6 10.00-12.30 P3 high path P.126 Matthijs Spaan, Coen Pieterse Monday 7/6 13.00-15.00 self-study path planning: Cspace Tuesday 8/6 10.00-12.30 P3 high path P.126 Matthijs Spaan, Coen Pieterse Tuesday 8/6 13.00-15.00 self-study path planning: structure Wednesday 9/6 10.00-12.30 P4 path to garbage P.126 Matthijs Spaan, Coen Pieterse Wednesday 9/6 13.00-15.00 L8 path planning: algorithms P.017 Leo Dorst Thursday 10/6 10.00-12.30 P5 low path P.126 Matthijs Spaan, Coen Pieterse Thursday 10/6 13.00-15.00 L9 rotations en homogeneous coördinates P.017 Leo Dorst Friday 11/6 'open dag op locatie'

Week 25

 Monday 14/6 10.00-12.30 P6 kinematics P.126 Matthijs Spaan, Coen Pieterse Monday 14/6 13.00-15.00 L11 kinematics: Denavit Hartenberg P.017 Leo Dorst Tuesday 15/6 10.00-12.30 P6 kinematics P.126 Matthijs Spaan, Coen Pieterse Tuesday 15/6 13.00-15.00 L12 inverse kinematics P.017 Leo Dorst Wednesday 16/6 10.00-12.30 P7 inverse kinematics P.126 Matthijs Spaan, Coen Pieterse Friday 18/6 10.00-16.00 P8 integration and demonstration Robotlab - F1.21, Kruislaan 403 Matthijs Spaan

Week 26

Go, where no one has gone before.

his time it is not the result that counts, but your summery of your survey. Document your progress, experiments and decisions in a LabBook.

 Monday 21/6 10.00-12.00 Experiment1 Kick-Off P.126 Arnoud Visser Wednesday 24/6 10.00-12.00 Experiment2 Mid-Term P.126 Arnoud Visser Friday 26/6 10.00-13.30 Experiment3 Demonstration and Documentation Robotlab - F1.21, Kruislaan 403 Arnoud Visser Friday 26/6 14.00-17.00 Experiment4 Grade & Drinks Euclides, Ground Floor Arnoud Visser

With a working system, and the acquired knowledge, you can explore new possibilities. Here are some suggestions:

• Extend the checkmate problem to more complex situations
• Play on a tilted board
• Play on a NewChess board
• Java implementation of the alpha-beta algorithm
• Use an Aibo as webcam
• Let the Aibo move one piece
• Create a 8x8 maze for the Aibo
• Create a maze for a plotter-robot
• Create 2D Game-interface with GameMaker.
It is recommanded to work in groups of three students.

You will be evaluated on your LabBook at the end of the week.

For the list of Labbooks of the 2004 students, see Experiment2004

## Results

The results can be found here.

## Evaluation

The course was overall evaluated by the participants with a 7.4.

## Literature

We start with chapter 13 and 22 of Prolog Programming for Artificial Intelligence by Ivan Bratko.

We continue with the second part of Introduction to AI Robotics by Robin Murphy: Navigation.
The University of Tennessee has a course that is also based on this textbook.

Further use lecture notes and a lab manual.

## Inheritance

In the old days, when Bachelors were not schooled at Dutch Universities, a different course was given with another focus. Still, much can be learned from the course 'Robotica'.

Last updated 28 July 2004

#### This web-page and the list of participants to this course is maintained by Arnoud Visser (arnoud@science.uva.nl)Faculty of ScienceUniversity of Amsterdam

 visitors in arnoud@science.uva.nl