This paper presents a fully autonomous navigation solution for urban, pedestrian environments. The task at hand, undertaken within the context of the European project URUS, was to enable two urban service robots, based on Segway RMP200 platforms and using planar lasers as primary sensors, to navigate around a known, large (10,000 m 2 ), pedestrian-only environment with poor global positioning system coverage. Special consideration is given to the nature of our robots, highly mobile but two-wheeled, self-balancing, and inherently unstable. Our approach allows us to tackle locations with large variations in height, featuring ramps and staircases, thanks to a three-dimensional, map-based particle filter for localization and to surface traversability inference for low-level navigation. This solution was tested in two different urban settings, the experimental zone devised for the project, a university campus, and a very crowded public avenue, both located in the city of Barcelona, Spain. Our results total more than 6 km of autonomous navigation, with a success rate on go-to requests of nearly 99%. The paper presents our system, examines its overall performance, and discusses the lessons learned throughout development. C 2011 Wiley Periodicals, Inc.

Abstract-We present to the robotic community a fully autonomous navigation solution for mobile robots operating in urban pedestrian areas. We introduce our robots and the experimental zone, overview the architecture of the navigation framework, and present the results after 3.5km of autonomous navigation. We expose the main lessons learnt by the scientific team and identify the issues to improve future works.