UAV-VLRR: 視覚言語情報を用いたNMPCによるUAV捜索救助の迅速応答
UAV-VLRR: Vision-Language Informed NMPC for Rapid Response in UAV Search and Rescue
視覚言語モデルとLLMでシーンを解釈し、障害物回避機能付き非線形モデル予測制御でドローンを飛行させる捜索救助システムを開発し、既存の自動操縦や人間のパイロットより高速な応答を実現した。
著者: Yasheerah Yaqoot, Muhammad Ahsan Mustafa, Oleg Sautenkov, Artem Lykov, Valerii Serpiva, Dzmitry Tsetserukou
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Emergency search and rescue (SAR) operations often require rapid and precise target identification in complex environments where traditional manual drone control is inefficient. In order to address these scenarios, a rapid SAR system, UAV-VLRR (Vision-Language-Rapid-Response), is developed in this research. This system consists of two aspects: 1) A multimodal system which harnesses the power of Visual Language Model (VLM) and the natural language processing capabilities of ChatGPT-4o (LLM) for scene interpretation. 2) A non-linearmodel predictive control (NMPC) with built-in obstacle avoidance for rapid response by a drone to fly according to the output of the multimodal system. This work aims at improving response times in emergency SAR operations by providing a more intuitive and natural approach to the operator to plan the SAR mission while allowing the drone to carry out that mission in a rapid and safe manner. When tested, our approach was faster on an average by 33.75% when compared with an off-the-shelf autopilot and 54.6% when compared with a human pilot. Video of UAV-VLRR: https://youtu.be/KJqQGKKt1xY
