Simultaneous localization and mapping using a micro-particle swarm optimization

Chris Monfredo, F. Sahin
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引用次数: 3

Abstract

Scan matching is a popular way of calculating a robot's position given range data corresponding to objects in the environment. This paper proposes a simultaneous localization and mapping algorithm that uses micro-particle swarm optimization as an alternative method to the traditional scan matching algorithms. The effectiveness of this algorithm is tested and compared to other popular simultaneous and localization algorithms.
利用微粒子群优化的同时定位和映射
扫描匹配是一种计算机器人位置的常用方法,它给出了与环境中物体相对应的距离数据。本文提出了一种基于微粒子群优化的同步定位与映射算法,作为传统扫描匹配算法的替代方案。对该算法的有效性进行了测试,并与其他流行的同步和定位算法进行了比较。
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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