Terrain-Aware Autonomous Exploration of Unstructured Confined Spaces

This work addresses the problem of exploring confined environments autonomously using terrestrial mobile robots. We propose a methodology for path planning in rough three-dimensional terrains and an exploration strategy that uses the map’s navigable areas, the related navigation cost, and the information expected from a frontier to select the next promising exploration sector. The safe path generation algorithm models the environment as a graph and uses a linear combination of weights applied to multiple traversability metrics of the terrain. The exploration phase uses the expected volumetric information of frontiers; this way, the exploration areas are selected according to their expected utility and visitation cost. We also propose an online planning phase using the raw point cloud to avoid obstacles. The online phase is faster to compute and uses the MI-RRT algorithm, an RRT-based planner biased towards the most informative frontier, capable of simultaneously planning and selecting a target frontier.