Semantic Robotics: Cooperative Labyrinth Discovery Robots for Intelligent Environments

Abstract

This chapter focuses on design, implementation. and utilization of semantic robots dealing with cooperative problem solving in a natural setting such as discovery of exit from a labyrinth. In our approach to realize this goal, a new modular architecture for designing and implementation of cooperative labyrinth discovery robots (CLDRs) is devised. Both hardware and software aspects are considered in detail. Robot and agent ontology aspects are treated in detail with examples. Likewise, labyrinth data structure (Maze Set) is represented in Notation 3 and OWL standard formats useful for purposes of semantic logic data processing in scientific software environments such as Prolog, Protege. and MATLAB. Concepts of Semantic Web technology are introduced leading to a working understanding of semantic Web services (SWS). A CLDR acts as an agent offering SWS. Each agent is an autonomous complex system, which acts based on its sensory input. information retrieved from other agents, and ontology files for agent and domain. CLDR decision making was introduced based on either of the principles of open/closed World assumptions. Messaging and coordination aspects are addressed. The approach is to create semantic robotic agents based on SWS to implement autonomous semantic agents (ASAs). Several applications can be built based on ASA architecture, where semantic robotics can play a vital part: traffic management, interactive traffic information dissemination, creating intelligent environment through intelligent intersections, dispatching vehicular services, and homeland security.