SOURCE-LINKED INTELLIGENCE
RAEM: Robust Autonomous Exploration for Multi-Floor Environments with a Quadruped Robot
In this paper, we propose RAEM, a robust autonomous exploration framework for quadruped robots operating in multi-floor environments. Most existing ground-robot exploration approaches rely on planar traversability representations, which cannot adequately represent the overlapping structures and cross-floor connectivity of multi-floor buildings. Although tomography-based representations provide effective traversability modeling for multi-floor navigation, maintaining a global tomography map incurs substantial computational overhead for online exploration with frequent replanning. Moreover, spar
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T04:40:34.000Z
First collected: 2026-09-21T09:22:01.459Z. This is not the publication date.