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Motion planning for actively reconfigurable mobile robots in search and rescue scenarios

In disaster scenarios, mobile robots can be employed in hazardous environments where it is too dangerous for human rescuers. Robotic systems can assist rescue personnel as they can be used to explore those inaccessible areas and to assess the situation. Tracked platforms with actuators have been proven to be well suited for such deployments because they are agile enough to overcome quite challenging terrain. A very demanding task for operators is the navigation of the robotic system in complex disaster environments. Hence, an important capability of future systems for search and rescue missions is autonomous navigation in disaster scenarios. In this paper we introduce a two-phase motion planning algorithm for tracked robots with actively controlled actuators to find a fast and stable path to a user specified goal. In the first phase, we generate an initial path considering the platform's operating limits and the terrain roughness. In the second phase, we limit the search space to the area around the initial path and refine the preliminary solution accounting for the complete robot state including actuators and the robot's stability and traction. A main distinction of our method is that it does not rely on a previous classification of the terrain, thus, can be applied to a variety of environments. We present experiments evaluating our algorithm in simulation and in two real-world scenarios to demonstrate the validity and feasibility of our approach.