# Abstract of FKI-192-94

Document-Name:  fki-192-94.ps.Z
Title:          Path Planning for Six-Joint  Manipulators
by Generalization from Example Paths
Authors:        Margit Kinder ,
Till Brychcy
Revision-Date:  1994/05/02
Category:       Technical Report (Forschungsberichte Künstliche Intelligenz)
Abstract:       This paper presents a novel kind of generalizing neural storage
tailored for the problem of global motion planning for
six-joint manipulators in complex, changing environments.
Paths are stored in a growing map of neurons with adaptive
ellipsoidal receptive field, called the {\em Ellipsoidal Map}.
Path planning is based on finding the best-matching neurons
for start and goal and a graph search in the neurons'
connectivity graph, which gets adapted to the topology of free
space. The Ellipsoidal Map remains adaptive all the time:
Paths can always be stored and information about collision in
planned paths, which occur in particular due to changes of the
environment, lead always to corrections of the map.  An
application to a simulation of the Rotex robot with six
degrees of freedom demonstrates highly satisfactory planning
skills.
Keywords:       ellipsoidal maps, graph of free space, generalizing storage,
6-joint manipulator, robot, path planning
Size:           8 pages
Language:       English
ISSN:           0941-6358
Copyright:      The Forschungsberichte Künstliche Intelligenz''
series includes primarily preliminary publications,
specialized partial results, and supplementary
material. In the interest of a subsequent final
publication these reports should not be copied. All
rights and the responsability for the contents of the
report are with the authors, which would appreciate