<title>Fast local mapping to support navigation and object localization</title>

Abstract

A robot must have an internal representation of the local space it occupies to use for both navigation and obstacle localization. In addition, it must be possible to build and update the map in real-time so that it can be used in feedback control loops. A robot's notion of local space must bridge the gap between symbolic and continuous control. To satisfy both real-time constraints and the needs of high-level navigation and object recognition, the map building system must use a simple representation that can be computed quickly yet will support the construction of more involved maps over longer timescales. A complete system also requires control behaviors that can use the simple representation to drive the robot through its immediate surroundings in service of higher-level local navigation goals generated from the more detailed map. This paper describes a system based on building simple geometric occupancy maps from multiple sensors in real-time and using them for control. The mapping and local navigation algorithms presented were used to control the University of Chicago mobile robot at the AAAI-92 Robot Competition.