Collaborative Planning for UAV-UGV Teams under Operational Constraints
Overview
A new neuro-symbolic diffusion framework, MEND, improves planning optimality for UAV-UGV teams by ensuring constraint compliance through error-bounded inference and logic-induced admissibility indicators, as shown in simulations and real-world tests. (2026-10-14).
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- arXiv Robotics — research abstractsCollaborative Planning for UAV-UGV Teams under Operational Constraints via Masked Error-bounded Neuro-Symbolic Diffusion
This research proposes MEND, a neuro-symbolic diffusion framework for collaborative planning in UAV-UGV teams under operational constraints. The method addresses limitations in existing masked diffusion models by incorporating error-bounded inference scheduling and logic-induced admissibility indicators to ensure constraint compliance during execution. Experimental results demonstrate improved planning optimality in simulation and real-world settings.
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