GapFlyt: 単眼カメラと機上センシングによる未知形状ギャップ検出とクアッドロータ飛行
GapFlyt: Active Vision Based Minimalist Structure-less Gap Detection For Quadrotor Flight
生物の知覚設計に着想を得て、3D再構成を行わず単眼カメラと機上センシングのみで未知の形状・位置の隙間を検出し、クアッドロータが通過するミニマリストな知覚-運動フレームワークを提案・実機検証した論文。
著者: Nitin J Sanket, Chahat Deep Singh, Kanishka Ganguly, Cornelia Fermüller, Yiannis Aloimonos
分類: cs.RO
原文アブストラクト
Although quadrotors, and aerial robots in general, are inherently active agents, their perceptual capabilities in literature so far have been mostly passive in nature. Researchers and practitioners today use traditional computer vision algorithms with the aim of building a representation of general applicability: a 3D reconstruction of the scene. Using this representation, planning tasks are constructed and accomplished to allow the quadrotor to demonstrate autonomous behavior. These methods are inefficient as they are not task driven and such methodologies are not utilized by flying insects and birds. Such agents have been solving the problem of navigation and complex control for ages without the need to build a 3D map and are highly task driven. In this paper, we propose this framework of bio-inspired perceptual design for quadrotors. We use this philosophy to design a minimalist sensori-motor framework for a quadrotor to fly though unknown gaps without a 3D reconstruction of the scene using only a monocular camera and onboard sensing. We successfully evaluate and demonstrate the proposed approach in many real-world experiments with different settings and window shapes, achieving a success rate of 85% at 2.5ms$^{-1}$ even with a minimum tolerance of just 5cm. To our knowledge, this is the first paper which addresses the problem of gap detection of an unknown shape and location with a monocular camera and onboard sensing.
