AUTONOMOUS BEHAVIOR-BASED EXPLORATION OF OFFICE ENVIRONMENTS

Abstract

Besides safe motion control the gain of environmental knowledge is a key for a reliable home or office service robot. When being set into a completely unknown environment the robot has to be able to derive a certain abstract internal representation of this world without any user interaction. This knowledge enables the robot to know how to get from its actual place in one room to a target position in another room as a prerequisite for transportation tasks for example. In this context, the combination of a behavior-based motion control system and an abstract topological map based on geometric representations of rooms seems promising. As the concept of motion and exploration behaviors facilitates to compete with noisy sensor information and geometrically imprecise maps, it has been used to develop completely autonomous exploration strategies for deriving topological representations of common indoor environments. The only prescribed world knowledge is the fact that these environments are composed of rectangular entities (rooms) which are connected by openings (doors). The developed system has successfully been tested in simulation and reality.