Keshavan J, Gremillion G, Escobar-Alvarez H, Humbert J S
Autonomous Vehicles Laboratory, Department of Aerospace Engineering, University of Maryland, College Park 20742, USA.
Bioinspir Biomim. 2014 Jun;9(2):025011. doi: 10.1088/1748-3182/9/2/025011. Epub 2014 May 22.
Safe, autonomous navigation by aerial microsystems in less-structured environments is a difficult challenge to overcome with current technology. This paper presents a novel visual-navigation approach that combines bioinspired wide-field processing of optic flow information with control-theoretic tools for synthesis of closed loop systems, resulting in robustness and performance guarantees. Structured singular value analysis is used to synthesize a dynamic controller that provides good tracking performance in uncertain environments without resorting to explicit pose estimation or extraction of a detailed environmental depth map. Experimental results with a quadrotor demonstrate the vehicle's robust obstacle-avoidance behaviour in a straight line corridor, an S-shaped corridor and a corridor with obstacles distributed in the vehicle's path. The computational efficiency and simplicity of the current approach offers a promising alternative to satisfying the payload, power and bandwidth constraints imposed by aerial microsystems.
在结构较少的环境中，让航空微系统实现安全、自主导航是当前技术难以攻克的挑战。本文提出了一种新颖的视觉导航方法，该方法将受生物启发的光流信息广域处理与用于闭环系统综合的控制理论工具相结合，从而实现了鲁棒性和性能保障。结构化奇异值分析用于合成动态控制器，该控制器在不确定环境中无需借助显式姿态估计或详细环境深度图提取即可提供良好的跟踪性能。四旋翼飞行器的实验结果表明，该飞行器在直线走廊、S形走廊以及飞行器路径上分布有障碍物的走廊中具有强大的避障能力。当前方法的计算效率和简易性为满足航空微系统所施加的 payload、功率和带宽限制提供了一种很有前景的替代方案。 （注：原文中“payload”未明确其在该语境下的准确含义，暂保留英文）
