Frontier-based Exploration on Continuous Radial Basis Function Neural Network Map

被引：0

作者：

Hou, Yuansong ^{[1
]}

Ruan, Xiaogang ^{[1
]}

Zhu, Xiaoqing ^{[1
]}

Li, Cheng ^{[1
]}

机构：

[1] Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100028, Peoples R China

来源：

2018 37TH CHINESE CONTROL CONFERENCE (CCC) | 2018年

关键词：

Mobile Robot; Frontier-Based Exploration; Radial Basis Function Neural Network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a frontier-driven autonomous robotic exploration method on a continuous representation of environment. The approach utilizes radial basis function neural network to build continuous occupancy grid map. Parametric frontiers are calculated directly by gradient field of occupancy probability distribution, which clear show division between free and unexplored space. Besides, the resulting frontiers provide a measure of quality automatically. Simulation is present to show the performance of the proposed technique.

引用

页码：5534 / 5538

页数：5

共 15 条

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