Abstract
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's capability profile. The resulting perception-sharing-planning loop feeds semantic corrections into traversability reasoning and replanning, forming an application-level mechanism motivated by AI-enabled goal-oriented communication envisioned for AI-native 6G networks. For the high-update case, transmitting semantic corrections reduces the application payload by a factor of approximately $82$ relative to periodic full-map sharing. Across matched benchmark scenarios, the proposed method achieved $91.5\%$ coverage with no capability-infeasible allocations, compared with $78.8\%$ coverage and a $21.5\%$ capability-infeasible allocation rate for LS-MCPP. Semantic corrections update the shared planning state without requiring repeated transmission of the complete map.
Keywords
Publication details
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- Green open access
Cite this article
APA 7
Dhafer, A., Wang, Q., & Hao, Z. D. (2026). Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination. https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination
MLA 9
Dhafer, Abdulqader, et al. "Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination." https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination.
Chicago (author–date)
Dhafer, Abdulqader, Qi Wang, and Zhou Daniel Hao. 2026. "Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination." https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination.
Harvard
Dhafer, A., Wang, Q. and Hao, Z. D. (2026) 'Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination', Available at: https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination.
Vancouver
Dhafer A, Wang Q, Hao ZD. Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination. https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination
IEEE
A. Dhafer, Q. Wang, and Z. D. Hao, "Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination," https://omanscience.com/en/articles/semantic-map-sharing-and-capability-aware-coverage-planning-for-ai-native-6g-robotic-coordination.