Unlocking Full Exploration Potential of Ground Robots by Multiresolution Topological Mapping

In this article, we propose a novel strategy leveraging multiresolution topological maps to guide ground robots in exploring complex 3-D environments. Our approach extracts traversable areas and local frontiers from detailed elevation maps and integrates them into a global multiresolution topological map with global frontiers and viewpoints. GPU-accelerated computation enhances efficiency, while a viewpoint-guided adaptive sampling mechanism generates a sparse global map for rapid path-length estimation to viewpoints. Collision-free global paths to target areas are computed efficiently using the multiresolution topological map. Extensive simulations with wheeled and legged robots demonstrate superior task completion rates and exploration efficiency compared to state-of-the-art methods, with further validation in real-world experiments. The code will be made publicly available to support the robotics community.