VLN on the Fly: An Onboard Vision-Language Navigation Stack for Aerial Robots
Running vision-language navigation fully onboard an aerial robot is hard, since grounding, planning, and control must share limited compute and a single-stage error is difficult to isolate in flight. End-to-end aerial policies fuse these stages into one network, giving up the observability and safety checks a modular stack keeps available. We propose VLN on the Fly, an onboard stack that keeps grounding, planning, and control as separate, inspectable stages. A quantized VLM grounds an instruction to a coarse image cell, depth lifts it to a 3D goal, a fast B-spline planner returns a feasible trajectory, and a pretrained reinforcement learning policy tracks it to motor commands across quadr...
| Authors | Marco S. Tayar, Felipe Tommaselli, Gianluca Capezutto et al. |
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| Primary category | cs.RO |
| Published | 7 August 2026 |
| Last updated at source | 7 August 2026 |
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