Adaptive Trajectory Planning for Safe Low-Level Helicopter Flight in MUM-T Environments

This article presents an adaptive trajectory planning approach for safe low-level helicopter flight in Manned-Unmanned Teaming (MUM-T) environments. The system combines real-time terrain data with environmental information gathered by sensors on scout UAVs operating ahead of the helicopter and employs modular long- and short-term optimization to generate dynamically feasible, tactically meaningful routes. The concept includes an integrated cockpit visualization that supports spatial awareness and enables pilots to use the generated routes effectively during low-altitude operations. We implemented the approach in a high-fidelity research simulator to enable early user involvement and iterative refinement. A multi-stage human-in-the-loop workshop with 13 experienced military pilots assessed usability, interpretability, and operational relevance. Pilots evaluated the routes as comprehensible and tactically sound and reported reduced mental load in low-level scenarios. Feedback highlighted the need for flexibility, transparency, and stability and yielded concrete guidance for improving the planning algorithms and interaction design. The study provides an initial, pilot-informed foundation for an integrated automation framework aimed at enhancing safety and mission effectiveness in demanding low-altitude operations.