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A μ analysis-based, controller-synthesis framework for robust bioinspired visual navigation in less-structured environments

机译:基于μ分析的,控制器综合框架,可在结构较少的环境中实现强大的生物启发式视觉导航

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摘要

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 controltheoretic 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.
机译:在结构较少的环境中,航空微系统进行安全,自主的导航是当前技术难以克服的挑战。本文提出了一种新颖的视觉导航方法,该方法将生物启发的光流信息的广域处理与控制理论工具相结合,以合成闭环系统,从而实现了鲁棒性和性能保证。结构奇异值分析用于合成动态控制器,该动态控制器在不确定的环境中提供良好的跟踪性能,而无需借助显式的姿态估计或详细的环境深度图的提取。四旋翼飞行器的实验结果证明了该车辆在直线通道,S形通道和在车辆路径中分布有障碍物的通道中的鲁棒避障性能。当前方法的计算效率和简便性为满足航空微系统施加的有效载荷,功率和带宽限制提供了一种有前途的选择。

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