日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2605.11296

Computational Design of a Low-Visibility UAV Using a Human-Aligned Perceptual Metric

Computational Design of a Low-Visibility UAV Using a Human-Aligned Perceptual Metric

シェア:XThreadsFacebookLINEはてブBluesky

著者: Jingxian Wang, Chen Yu, David Matthews, Emma Alexander, Sam Kriegman, Michael Rubenstein

分類: cs.RO, cs.SY, eess.SY

原文アブストラクト

We introduce Phantom Twist, a type of single-propeller UAV designed to achieve low visibility through high-speed spinning and the exploitation of motion blur. We develop a two-stage automated design pipeline that optimizes the placement of functional components including batteries, control PCB, motor-propeller assembly, and counterweights. The pipeline minimizes visibility as measured by a human-aligned perceptual metric (LPIPS) while strictly satisfying inertial and aerodynamic constraints required for stable flight. We validate this approach through fabrication and flight testing of multiple prototypes. These tests confirm that our pipeline produces stable, controllable designs and that the optimized UAV exhibits significantly reduced visual perceptibility compared to conventional quadcopters.