Bug-based T2: A New Globally Convergent Potential Field Approach to Obstacle Avoidance

Abstract

Reactive mobile robot navigation based on potential field methods has shown to be a good solution for dealing with both unknown and dynamic environments, where timely responses are required. Unfortunately, the complexity of the tasks which can be successfully carried out is restricted by the inherent shortcomings of the approach such as trapping situations due to local minima, difficulties passing among closely spaced obstacles, oscillations in narrow corridors, etc. The first of the aforementioned limitations was fully overcome in J. Antich and A. Ortiz (2005) by applying the two new principles of traversability and tenacity in the context of artificial potential fields. As a result, navigation was achieved in very difficult scenarios, even including maze-like environments. In this paper, continuing that previous work, it is intended to step forward by ensuring, whenever possible, that the target point is attained for any mission, setting, at the same time, an upper bound regarding the length of the resultant robot's path