Robot localisation using interval analysis

I. Ashokaraj, A. Tsourdos, B. White, P. Silson
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引用次数: 3

Abstract

This paper describes a deterministic approach for the sensor-based localisation and navigation of a mobile robot. This approach is based on interval analysis and the robot equipped with ultrasonic sensors. For the localisation, it is assumed that the map is 2D and also it is assumed to be known a-priory to the robot. It has already been shown by Jaulin et.al. that mobile robot localisation and tracking using interval analysis and an interval model of the robot, with ultrasonic sensors only can be achieved. Here we use the same algorithm for robot localisation but without using an interval model of the robot. Instead the physical limitations of the robot is used to predict and track the robots position. In classical methods such as Kalman filters for robot localisation, the data association step is very complex and they are based on linearisation. Where as the method proposed here using interval analysis bypasses the data association step and deals with the problem as nonlinear and in a global way.
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使用区间分析的机器人定位
本文描述了一种基于传感器的移动机器人定位和导航的确定性方法。该方法是基于区间分析和机器人配备超声波传感器。对于定位,假设地图是2D的,并且假设它是机器人优先知道的。Jaulin等人已经证明了这一点。认为移动机器人的定位和跟踪利用区间分析和机器人的区间模型,只有用超声波传感器才能实现。这里我们使用相同的算法来定位机器人,但没有使用机器人的区间模型。相反,机器人的物理限制被用来预测和跟踪机器人的位置。在经典的机器人定位方法中,如卡尔曼滤波,数据关联步骤非常复杂,并且是基于线性化的。而本文提出的区间分析方法则绕过了数据关联步骤,以全局的非线性方式处理问题。
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