A Common Sense Knowledge Framework For Subsystem Autonomy

Abstract

Many robot motion planning algorithms treat the environment in which a robot operates as a meaningless world, that is, a two (or three) -dimensional space filled with obstacles described by geometric functions. For example, some formulate the navigation problem as directing the robot from one place in the space to another without concerning themselves with things such as how the robot decides where it wants to go based on higher level considerations. In order to make a robot truly autonomous, it is necessary to incorporate appropriate knowledge representation and reasoning capabilities in the planning framework. A frame-based knowledge representation and reasoning system, WenLy, is presented in this paper. We will examine the design issues of a knowledge system and specific considerations in WenLy. The structure of knowledge and reasoning mechanisms will be given special attention. We will first present our view of knowledge and knowledge representation, which is very important to the formation of our approach. Then, we will introduce the frame-based system WenLy with some discussions in the structure as a reflection of our view of knowledge. Finally, we will examine some features in WenLy (including other knowledge representation systems) and relate them with the development of knowledge.