Applying means-ends analysis to spatial planning

Currently known methods for robot planning fall far behind human capabilities: they require approximations of shapes, and they cannot generate plans which involve moving obstacles to clear a path for the moving object. In this paper, we explore the hypothesis that means-ends analysis based on a world model involving mental imagery allows more human-like solutions. Our method is based on a novel way of representing planning constraints which makes it possible to incrementally generate the symbolic representations for means-ends planning using only imagery operations.


Year:
1992
Publisher:
Publ by IEEE, Piscataway, NJ, USA
Keywords:
Note:
Ecole Polytechnique Federale de Lausanne, Lausanne, Switz
Laboratories:




 Record created 2008-01-14, last modified 2018-03-17


Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)