Efficient Autonomous Navigation of a Quadruped Robot in Underground Mines on Edge Hardware

• URL: http://arxiv.org/abs/2603.04470v1
• Date: Wed, 04 Mar 2026 02:23:55 GMT
• Title: Efficient Autonomous Navigation of a Quadruped Robot in Underground Mines on Edge Hardware
• Abstract summary: Embodied navigation in underground mines faces significant challenges, including narrow passages, uneven terrain, near-total darkness, GPS-denied conditions, and limited communication infrastructure.<n>We present a fully autonomous navigation stack for a Boston Dynamics Spot robot that runs entirely on a low-power Intel computer edge with no GPU and no network connectivity requirements.<n>We validate the system through repeated field trials using four target locations of varying difficulty in an experimental underground mine, accumulating over 700 m of fully autonomous traverse with a 100% success rate across all 20 trials.
• Score: 0.5371337604556311
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Embodied navigation in underground mines faces significant challenges, including narrow passages, uneven terrain, near-total darkness, GPS-denied conditions, and limited communication infrastructure. While recent learning-based approaches rely on GPU-accelerated inference and extensive training data, we present a fully autonomous navigation stack for a Boston Dynamics Spot quadruped robot that runs entirely on a low-power Intel NUC edge computer with no GPU and no network connectivity requirements. The system integrates LiDAR-inertial odometry, scan-matching localization against a prior map, terrain segmentation, and visibility-graph global planning with a velocity-regulated local path follower, achieving real-time perception-to-action at consistent control rates. After a single mapping pass of the environment, the system handles arbitrary goal locations within the known map without any environment-specific training or learned components. We validate the system through repeated field trials using four target locations of varying traversal difficulty in an experimental underground mine, accumulating over 700 m of fully autonomous traverse with a 100% success rate across all 20 trials (5 repetitions x 4 targets) and an overall Success weighted by Path Length (SPL) of 0.73 \pm 0.09.

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