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Challenges and Opportunities for Large-Scale Exploration with Air-Ground Teams using Semantics

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arxiv 2405.07169 v1 pith:T354VEON submitted 2024-05-12 cs.RO

classification cs.RO
keywords challengesexplorationsystemair-groundapproachlarge-scalerobotssemantics
verification ladder T0 review T1 audit T2 compute T3 formal
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One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressing such exploration challenges. In this paper, we demonstrate a system for large-scale exploration using a team of aerial and ground robots. Our system uses semantics as lingua franca, and relies on fully opportunistic communications. We highlight the unique challenges from this approach, explain our system architecture and showcase lessons learned during our experiments. All our code is open-source, encouraging researchers to use it and build upon.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Semantics-aware Predictive Inspection Path Planning

    cs.RO 2025-06 conditional novelty 6.0 of 10

    A semantics-aware inspection planner that predicts repeated structures in unseen space reduces mission time by 12 to 19 percent in real ballast tanks while maintaining coverage.

  2. Communication-Aware Map Compression for Online Path-Planning: A Rate-Distortion Approach

    cs.RO 2025-06 conditional novelty 4.0 of 10

    A scout robot compresses its map with a rate-distortion optimization whose closed-form reverse water-filling solution sends only the regions relevant to a ground robot's planned path.

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