単眼カメラと模倣学習による森林環境での小型ドローンの自律飛行
Learning Monocular Reactive UAV Control in Cluttered Natural Environments
小型クアッドロータが単眼カメラのみで森林内を最大1.5m/sで自律飛行できるよう、人間の操縦デモから模倣学習で障害物回避コントローラを訓練した研究。
著者: Stephane Ross, Narek Melik-Barkhudarov, Kumar Shaurya Shankar, Andreas Wendel, Debadeepta Dey, J. Andrew Bagnell, Martial Hebert
分類: cs.RO, cs.CV, cs.LG, cs.SY, eess.SY
原文アブストラクト
Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward, as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAVs) which operate at low altitude in cluttered environments. Unlike large vehicles, MAVs can only carry very light sensors, such as cameras, making autonomous navigation through obstacles much more challenging. In this paper, we describe a system that navigates a small quadrotor helicopter autonomously at low altitude through natural forest environments. Using only a single cheap camera to perceive the environment, we are able to maintain a constant velocity of up to 1.5m/s. Given a small set of human pilot demonstrations, we use recent state-of-the-art imitation learning techniques to train a controller that can avoid trees by adapting the MAVs heading. We demonstrate the performance of our system in a more controlled environment indoors, and in real natural forest environments outdoors.
