Dynamic diagrammatic representations for reasoning and motion control

Abstract

The aim of this paper is to propose a way of performing spatial reasoning about dynamic scenarios. We describe a class of intrinsically dynamic diagrammatic models, that are based on the metaphor of artificial potential fields (APFs). APFs are a well known method used for motion planning and force control in robotics. We show that the use of APFs can be extended to different domains, in order to face various problems of spatial reasoning and planning. An advantage of this approach is the lack of a clear cut boundary between reasoning and control. This allows a better integration of these two aspects. In the present paper, this claim is exemplified on grasping problems.