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.

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