Dynamics maps for long-term autonomy

Navigating is one of the most basic capabilities of mobile robots. For this task, robots usually represent the environment through maps. This paper reports on first results of a work focused on mapping dynamic environments to achieve a robust navigation for long-term operation. This approach builds a static map starting from the construction plans of a building. A long-term map is started from the static map, and updated when adding and removing furniture, or when doors are opened or closed. A short-term map represents dynamic obstacles such as people. This approach is appropriate for fast deployment and long-term operations in office or domestic environments, able to adapt to changes in the environment. We demonstrate the robustness of this approach in the RoboCup@home competition, where robots must navigate in an environment that changes during the tests.