This research proposes an onboard vision-language navigation stack for aerial robots. VLN on the Fly separates grounding, planning, and control into distinct stages, improving observability and safety. The stack uses a quantized VLM to ground instructions, a B-spline planner for trajectory generation, and a pretrained reinforcement learning policy for motor command tracking.