Autonomous Robot Navigation in Highly Populated Pedestrian Zones

TLDR

Autonomous robot navigation has progressed indoors and on roads, yet few systems tackle the unstructured, dynamic challenges of urban city centers. The paper introduces a navigation system for mobile robots tailored to crowded city pedestrian zones. The system integrates a large‑scale SLAM module, terrain‑aware path planning, dynamic‑environment localization, and platform calibration and monitoring. Field tests demonstrate the robot autonomously traversing several kilometers in complex urban settings, including a 3‑km public demonstration in Freiburg, Germany.

Abstract

In the past, there has been a tremendous amount of progress in the area of autonomous robot navigation, and a large variety of robots have been developed that demonstrated robust navigation capabilities indoors, in nonurban outdoor environments, or on roads; relatively few approaches have focused on navigation in urban environments such as city centers. Urban areas, however, introduce numerous challenges for autonomous robots as they are rather unstructured and dynamic. In this paper, we present a navigation system for mobile robots designed to operate in crowded city environments and pedestrian zones. We describe the different components of this system, including a simultaneous localization and mapping module for dealing with huge maps of city centers, a planning component for inferring feasible paths, taking into account the traversability and type of terrain, a module for accurate localization in dynamic environments, and the means for calibrating and monitoring the platform. Our navigation system has been implemented and tested in several large‐scale field tests, in which a real robot autonomously navigated over several kilometers in a complex urban environment. This also included a public demonstration, during which the robot autonomously traveled along a more than 3‐km‐long route through the city center of Freiburg, Germany.