Frontier-Based Probabilistic Strategies for Sensor-Based Exploration

Abstract

We present a frontier-based modification of the SRT (Sensor-based Random Tree) method, a previously proposed probabilistic strategy for sensor-based exploration of unknown environments by a mobile robot. The idea is to improve the efficiency of the method by biasing the randomized generation of configurations towards unexplored areas. Effective implementations of this strategy are proposed for SRT-Ball and SRT-Star, two instances of the general SRT method corresponding to different perception attitudes and sensing equipments. Comparative simulations are presented to show the benefits of the proposed technique.