Long-term Ground Robot Localization Architecture for Mixed Indoor-Outdoor Scenarios

Abstract

This paper summarizes the validation and experimental results of an architecture for six degree-of-freedom robot localization developed in the framework of the EC funded project FROG (FP7-ICT-2011.2.1). Two main localization issues are considered; one is accuracy, required by the Augmented Reality application, and the second is robustness, in order to achieve long-term autonomy of the robot. The experiments were carried out mainly at the Lisbon Zoo (Portugal), a low GPS visibility area with more than 40,000 square meters and non-planar routes as long as 1 kilometer. The approach considers an offline SLAM and multi-sensor data fusion for map building, and a Rao-Blackwellized filter for online robot localization based on previously computed map. The approach also considers localization failures and provides a method for robot re-localization based on visual place recognition.