Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination
Search and Rescue (SAR) operations increasingly deploy heterogeneous teams of aerial and ground robots. However, conventional coverage methods typically do not translate perceived terrain into platform-specific reachability, while continuous image exchange imposes a high communication cost. We propose an edge-centric, semantic-aware coverage planning framework that integrates aerial terrain perception, robot-specific traversability reasoning, and payload-efficient semantic state sharing. Aerial observations are converted into compact semantic grid maps, enabling reachability-constrained area decomposition and capability-aware coverage paths that assign only regions admitted by each robot'...
| Authors | Abdulqader Dhafer, Qi Wang, Zhou Daniel Hao |
|---|---|
| Primary category | cs.RO |
| Published | 29 September 2026 |
| Last updated at source | 29 September 2026 |
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