The chair
Research mainly focusses on computer architectures for Computational Intelligence by making use of the following methods and fields of application:Artificial Neural Networks
Research
is done here on neural net simulation which has begun with the development
of the Stuttgart Neural
Network Simulator. Neural nets are used for classification,
parameter identification, control and prediction in technical applications
(e.g. for motor optimization)
and they are applied in bioinformatics (e.g. for searching
and optimizing lead compounds). A multimedia training course
on neural networks is developed in the project VirtuGrade
(Baden-Württemberg).
Evolutionary Algorithms
In
the EvA project (evolutionary
algorithms) a system was developed combining several sequential
and parallel variants of genetic algorithms (GA) and evolution strategies
(ES).
EvA runs on Linux PCs, Unix workstations, WS clusters and parallel
computers.
EvA is used in a number of projects in cooperation with industry,
e.g. in order to optimize
the position of fixation tools or for motor
optimization . A multimedia training course on evolutionary
algorithms is developed in the project Bioinform@tik
.
Autonomous Mobile Robots
Research aims at image processing, sensor fusion, navigation, path
planning and the control of mobile robots here. Future service robots
shall be able to recognize people and to interact intelligently
with users. Our robot lab operates two mobile robots RWI B21 (Robin
and Colin) by Real World Interface,
Inc. with stereo cameras, 2D laser scanner, ultrasonic detectors
and infrared sensors and an outdoor
robot RWI ATRV-Jr.
In order to do research on artificial
life 5 small robots Pioneer1
and one PioneerAT by ActivMedia,
Inc. are used. After they had been modified for playing robot
soccer they claimed the vice world championship at RoboCup-98.
Bioinformatics Applications
A
series of application areas for bioinformatics is tested here together
with partners from chemistry and biochemistry as well as biology.
The BMBF research projects automated
combinatorial chemistry and search
and optimization of lead compounds are counted among them as
well as the analysis of planar biological neural networks by means
of artificial neural networks. Concerning the project Bioinform@tik
teaching material is developed here for the new study course
Bioinformatics.

