Online self-reconfigurable robot navigation in heterogeneous environments

This paper presents a robot navigation system capable of online self-reconfiguration according to the needs imposed by the various contexts present in heterogeneous environments. The ability to cope with heterogeneous environments is key for a robust deployment of service robots in truly demanding scenarios. In the proposed system, flexibility is present at the several layers composing the robot´s navigation system. At the lowest layer, proper locomotion modes are selected according to the environment´s local context. At the highest layer, proper motion and path planning strategies are selected according to the environment´s global context. While local context is obtained directly from the robot´s sensory input, global context is inspected from semantic labels registered off-line on geo-referenced maps. The proposed system leverages on the well-known Robotics Operating System (ROS) framework for the implementation of the major navigation system components. The system was successfully validated over approximately 1 Km long experiments on INTROBOT, an all-terrain industrial-grade robot equipped with four independently steered wheels.