基于粒子滤波的全向视觉定位

Zuo-liang Cao, Shiyu Liu, J. Roning
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引用次数: 26

摘要

全方位视觉导航以其单一紧凑视觉场景的全景式视觉优势显得尤为重要。这种独特的制导技术包括目标识别、视觉跟踪、目标定位和路径规划。提出了一种利用两个开销特征作为信标模式的全局视觉全局定位算法。由于全视图像存在固有的失真,必须考虑一种几何恢复方法。机器人的定位可以通过几何计算来实现。动态定位采用信标跟踪器,在车辆的任意运动过程中实时跟踪地标。粒子滤波(PF)已被证明是成功的非线性估计问题。提出了一种基于粒子滤波的信标跟踪器,为视觉跟踪中的动态状态估计提供了一个概率框架。我们实现了跟踪和定位系统,并演示了算法的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Omni-directional Vision Localization Based on Particle Filter
Omni-directional vision navigation appears definite significant since its advantage of panoramic sight with a single compact visual scene. This unique guidance technique involves target recognition, vision tracking, object positioning, path programming. An algorithm for omni-vision based global localization which utilizes two overhead features as beacon pattern is proposed in this paper. An approach for geometric restoration of omni-vision images has to be considered since an inherent distortion exists. The localization of the robot can be achieved by geometric computation. Dynamic localization employs a beacon tracker to follow the landmarks in real time during the arbitrary movement of the vehicle. Particle filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on Particle filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. We have implemented the tracking and localization system and demonstrated the relevant of the algorithm.
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