On Motion Planning with Uncertainty

Item

Title
en_US On Motion Planning with Uncertainty
Creator
en_US Erdmann, Michael Andreas
Date
2004-10-20T20:10:12Z
Date Available
2004-10-20T20:10:12Z
Date Issued
en_US 1984-08-01
Identifier
en_US AITR-810
uri
http://hdl.handle.net/1721.1/6949
Abstract
en_US Robots must successfully plan and execute tasks in the presence of uncertainty. Uncertainty arises from errors in modeling, sensing, and control. Planning in the presence of uncertainty constitutes one facet of the general motion planning problem in robotics. This problem is concerned with the automatic synthesis of motion strategies from high level task specification and geometric models of environments. In order to develop successful motion strategies, it is necessary to understand the effect of uncertainty on the geometry of object interactions. Object interactions, both static and dynamic, may be represented in geometrical terms. This thesis investigates geometrical tools for modeling and overcoming uncertainty. The thesis describes an algorithm for computing backprojections o desired task configurations. Task goals and motion states are specified in terms of a moving object's configuration space. Backprojections specify regions in configuration space from which particular motions are guaranteed to accomplish a desired task. The backprojection algorithm considers surfaces in configuration space that facilitate sliding towards the goal, while avoiding surfaces on which motions may prematurely halt. In executing a motion for a backprojection region, a plan executor must be able to recognize that a desired task has been accomplished. Since sensors are subject to uncertainty, recognition of task success is not always possible. The thesis considers the structure of backprojection regions and of task goals that ensures goal recognizability. The thesis also develops a representation of friction in configuration space, in terms of a friction cone analogous to the real space friction cone. The friction cone provides the backprojection algorithm with a geometrical tool for determining points at which motions may halt.
Extent
30174250 bytes
11286190 bytes
Format
application/postscript
application/pdf
Language
en_US
Relation
en_US AITR-810
Item sets
AI Technical Reports (1964 - 2004)