Cognitive robot mapping with polylines and an absolute space representation

Robot mapping even today is one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid to represent a mapped region. This approach becomes problematic if the robot is mapping a large environment, the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with sonars) sees the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a room by room fashion. As the robot leaves a space, denoted by passing through a doorway, the grids are converted to a polygonal representation. This polygonal representation is stored as rooms and hallways as a set of Absolute Space Representations (ASRs) representing the space connections. Using this representation makes navigation and localization easier for the robot to process.