Exploring information theory for vision-based volumetric mapping

被引：0

作者：

Rocha, R ^{[1
]}

Dias, J ^{[1
]}

Carvalho, A ^{[1
]}

机构：

[1] Univ Coimbra, Fac Sci & Technol, Inst Syst & Robot, P-3030290 Coimbra, Portugal

来源：

2005 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4 | 2005年

关键词：

3-D volumetric mapping; entropy; probabilistic maps; mapping and exploration; stereo-vision sensors;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article presents an innovative probabilistic approach for building volumetric maps of unknown environments with autonomous mobile robots, which is based on information theory. Each mobile robot uses an entropy gradient-based exploration strategy, with the aim of maximizing information gain when building and improving a 3-D map upon measurements yielded by an on-board stereo-vision sensor. The proposed framework was validated through experiments with a real mobile robot equipped with stereo-vision, in order to be further used on cooperative volumetric mapping with teams of mobile robots.

引用

页码：2409 / 2414

页数：6

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