Indoor exploration using a sonar sensor array: a dual representation strategy

Abstract

This paper presents an environmental acquisition strategy for a mobile robot using an advanced sonar sensor to achieve mapping navigation in an a priori unknown, imperfectly structured indoor environment. Most existing feature based strategies rely on unrealistic assumptions about the environment, while their grid based counterparts hinder localisation which leads to rapid degradation of map quality. A dual representation strategy is proposed here which exploits the strength of both a feature map and a grid map. With the advantage sensor, the environment is scanned and the obtained features are classified into planes, corners, edges and unknowns. The feature map is only updated with the first three types of features. The grid map is updated with all measurement, including the unknowns resulting from complicated objects, to enable obstacle avoidance. On the grid map, distance transform based exploratory path planning is implemented. Adaptation has been made so that an explore-local-first behaviour is exhibited.