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Landmark-Based Particle Localization Algorithm for Mobile Robots With a Fish-Eye Vision System

机译:基于地标的鱼眼视觉移动机器人粒子定位算法

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Localization is a crucial ability for autonomous robots and landmark-based localization can be effectively used because it enables localization with only landmark information. For localization, the omnidirectional vision system is efficiently used for robots to obtain information of the surrounding environment, but it is expensive and has some distortion. In this sense, the fish-eye lens vision system can be an alternative. Compared to the omnidirectional vision system, however, it obtains less landmark information at a time so that it needs a localization algorithm using less landmark information. To solve this problem, this paper proposes a novel landmark-based particle localization algorithm for the global localization problem called relocation. It can localize the pose of the robot using only two landmarks. In this algorithm, information on bearing angle and distance of landmarks is used to calculate a possible area of the location of the robot and then particles, each of which represents a pose of the robot, are randomly distributed in the calculated area. The pose of the robot is identified by selecting a particle with the highest importance weight among the distributed particles. Computer simulations and experiments demonstrate the effectiveness of the proposed algorithm.
机译:本地化是自主机器人的一项关键功能,基于地标的本地化可以有效地使用,因为它仅允许使用地标信息进行定位。为了进行定位,全向视觉系统被有效地用于机器人获取周围环境的信息,但是它昂贵并且存在一些失真。从这个意义上讲,鱼眼镜头视觉系统可以替代。但是,与全向视觉系统相比,它一次获取的地标信息较少,因此需要使用较少地标信息的定位算法。为了解决这个问题,本文针对全局定位问题提出了一种新颖的基于地标的粒子定位算法,称为重定位。它可以仅使用两个界标来定位机器人的姿势。在该算法中,有关方位角和界标距离的信息用于计算机器人位置的可能区域,然后每个代表机器人姿势的粒子随机分布在计算区域中。通过选择分布的粒子中具有最高重要权重的粒子,可以识别机器人的姿势。计算机仿真和实验证明了该算法的有效性。

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