Precise Coordinated Localization for Swarm Robots via Multidimensional Scaling and Wireless Sensor Networks

Xuefei Wu, Han Wu, Bo Xin, Chunlin Chen
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引用次数: 1

Abstract

Precise localization has always been a fundamental and vital problem for swarm robots to perform their tasks. In this work we propose a solution with both efficiency and practicability. Iterative multidimensional scaling (MDS) technique and wireless sensor networks (WSN) are combined to achieve accurate localization and auxiliary formation control. Iterative MDS algorithm is utilized to obtain the topology of the robot swarm, i.e., relative positions of all the robots. Radio frequency identification (RFID) is used as reference in the following coordinate transformation process. Then the global localization is achieved with high precision. With a better knowledge of the position of each other, the robots are able to maintain a more orderly formation during movement. The advantages of this method are that the initial point of iteration process is optimized and reference nodes are acquired in an efficient and reliable way. Simulation results have proved the success of the proposed approach.
基于多维尺度和无线传感器网络的群体机器人精确协调定位
精确定位一直是群机器人执行任务的基础和关键问题。在这项工作中,我们提出了一个既高效又实用的解决方案。将迭代多维标度(MDS)技术与无线传感器网络(WSN)相结合,实现精确定位和辅助编队控制。利用迭代MDS算法获得机器人群的拓扑结构,即所有机器人的相对位置。在接下来的坐标转换过程中,使用射频识别(RFID)作为参考。实现了高精度的全局定位。通过更好地了解彼此的位置,机器人能够在运动过程中保持更有序的队形。该方法的优点是优化了迭代过程的起始点,有效可靠地获取了参考节点。仿真结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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