PhD thesis "Adaptive Approaches to Basic Mobile Robot Tasks" available

[Uwe R. Zimmer, AG vP]

PhD thesis available via WWW / FTP:

keywords: mobile robots, exploration, world modelling, navigation, 
object recognition, artificial neural networks, fuzzy logic

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         Adaptive Approaches to Basic Mobile Robot Tasks
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                         Uwe R. Zimmer

                    PhD thesis - January 1995


The present thesis addresses the research field of adaptive 
behaviour concerning mobile robots. The world as "seen" by the 
robot is previously unknown and has to be explored by manoeuvring 
according to certain optimization criteria. This assumption 
enhances the fitness of a mobile robot for a range of applications 
beyond rigid installations, demanding normally significant effort, 
and offering limited ability to adapt to changes in the 
environment.
A central concept emphasized in this thesis is the achieving of 
competence and fitness through continuous interaction with the 
robot's world. Lifelong learning is considered, even after 
achieving a temporally sufficient degree of adaptation and running 
in parallel to the actual robot's application. The levels of 
competence are generated bottom up, i.e. upper levels are based on 
the current robot's experience modelled in lower levels. The terms 
(the skills are formulated with) employed on higher levels are 
generated through real world interactions on lower levels.
The robotics problems discussed are limited to some basic tasks, 
which are found to be relevant for most mobile robot applications. 
These are exploration of unknown environments, stable 
self-localization with respect to the current world and its 
internal representation, as well as navigation, target extraction, 
and target recognition.
In order to cope with problems resulting from a lack of proper 
a-priori knowledge and defined and reliably detectable symbols in 
unknown and dynamic environments, connectionist methods are 
employed to a great extend. Realtime constraints are considered at 
all levels of competence, with the natural exception of global 
planning. 
The research field of target extraction and identification with 
respect to mobile robot constraints leads especially to the 
discussion of visual search (steering), extraction of geometric 
primitives even at system start-up time, and to the generation of 
symbols out of subsymbolic processing. These symbols can be 
reliably recognized and should be suitable for a following 
symbolic planning level, outside the focus of the present thesis. 
The presented approach ensures a large degree of adaptability on 
all levels, not discussed before to this wide extent, or even 
investigated for the first time regarding some components (e.g. 
visual search with highly focused devices).
The exploration, self-localization, and navigation tasks are 
attacked by an integral approach allowing the parallel processing 
of these tasks in a dynamic environment. The stability and 
reliability of the discussed techniques are proven on the base of 
realtime and real world experiments with a mobile platform. The 
high error tolerance and low demands concerning the used sensor 
devices, as well as the small computation power required, are 
(currently) unique features of the presented method.

Files:

   - Part I   : Introduction          - 24 pages, 0.9 MB
   - Part II  : ALICE                 - 30 pages, 2.0 MB
   - Part III : SPIN                  - 60 pages, 1.6 MB
   - Part IV  : Conclusion & Appendix - 38 pages, 0.9 MB
   
for the WWW-links to the files of this thesis:

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http://ag-vp-www.informatik.uni-kl.de/Projekte/ALICE/abs.PhD.html
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for the homepage of the author (including more reports):

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http://ag-vp-www.informatik.uni-kl.de/Leute/Uwe/
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or for the ftp-server hosting the files:

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ftp://ag-vp-ftp.informatik.uni-kl.de/Public/Neural_Networks/
Reports/Zimmer.PhD/ ...
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                                                       ----- 
   Uwe R. Zimmer                                              ---
     University of Kaiserslautern - Computer Science Department  |
     67663 Kaiserslautern - Germany                              |
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     Phone:+49 631 205 2624     |     Fax:+49 631 205 2803       |
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         http://ag-vp-www.informatik.uni-kl.de/Leute/Uwe/        |