Planning Topological Navigation for Complex Indoor Environments

The ability to move around the environment is one of the most important capabilities of a mobile robot. Although navigation is considered an already achieved capacity, there is still much work to be done to integrate navigation with high level reasoning and acting. Navigate in indoor environments also involve complex actions, such as opening doors, use elevators, and many others. We propose a topological navigation system based on Artificial Intelligence (AI)Planning. Starting from a symbolic representation of the environment, navigation tasks are divided into phases, in which different actions are required. This approach has demonstrated to be very effective to plan the operations of a robot at indoor environments. The final result is method compact, efficient and scalable. Our system has been successfully tested at European Robotics League in the humanoid robot Pepper.