Real-time autonomous 3D navigation for tracked vehicles in rescue environments

The paper presents a novel framework for 3D autonomous navigation for tracked vehicles. The framework takes care of clustering and segmentation of point clouds, traversability analysis, autonomous 3D path planning, motion planning and flippers control. Results illustrated in an experiment section show that the framework is promising to face harsh terrains. Robot performance is proved in three main experiments taken in a training rescue area, on fire escape stairs and in a non-planar testing environment, built ad-hoc to prove 3D path planning functionalities. Performance tests are also presented.

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