Arrangement map for task planning and localization for an autonomous robot in a large-scale environment

Abstract

This paper presents a planning approach for solving the global localization problem using an arrangement of rooms to compress the original map. The approach is based on architectural design features of the building such as walls and doors to help the robot on finding the best route to go. Lighter POMDP plans are generated only for representative rooms of the environment, decreasing size of the set of possible states. The plans are created offline only once and used indefinitely regardless of missions combining them online. The plan only requires as input, the environment map and the robot actions and possible observations. We demonstrate the single level approach and the map decomposition with experiments on both V-REP Simulator and the Pioneer 3DX robot. This approach allows the robot to perform both the localization and tasking in a large-scale environment.