网络化多机器人系统的在线局部边界检测与分类算法

2016 International Conference on Advanced Technologies for Communications (ATC) Pub Date : 2016-10-01 DOI:10.1109/ATC.2016.7764783

Pham Duy Hung, T. Q. Vinh, T. Ngo

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引用次数: 1

摘要

针对网络多机器人系统，提出了一种在线边界分类错误检测算法，以提高原有分布式边界检测算法的准确性。它是一种基于几何方法的完全去中心化方法，可以抑制边界误差，不需要递归过程和全局同步。正确识别的机器人比例占机器人总数的准确率达到100%。我们已经在仿真和现实环境中证明了这种边界检测算法的有效性。

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An online local boundary detection and classification algorithm for networked multi-robot systems

We present an online boundary classification error detection algorithm to improve accuracy of the original distributed boundary detection algorithm for networked multirobot systems. It is a fully decentralized method based on the geometric approach allowing to suppress boundary errors without recursive process and global synchronization. The accuracy of the ration of correctly identified robots over the total number of robots reaches 100%. We have demonstrated the effectiveness of this boundary detection algorithm in both simulation and real-world environment.

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来源期刊

2016 International Conference on Advanced Technologies for Communications (ATC)

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