Mobile Robot Neuro-fuzzy Navigation Based VSLAM Features Learning

被引：0

作者：

Mattar, Ebrahim ^{[1
]}

AlMutib, Khalid ^{[2
]}

AlSulaiman, Mansour ^{[2
]}

Ramdane, Hajar ^{[2
]}

机构：

[1] Univ Bahrain, Coll Engn, POB 32038, Sukhair, Bahrain

[2] King Saud Univ, Coll Comp & Informat Sci, POB 51178, Riyadh, Saudi Arabia

来源：

2017 9TH IEEE-GCC CONFERENCE AND EXHIBITION (GCCCE) | 2018年

关键词：

Mobile Robots; Neuro-Fuzzy; Intelligent Navigation; Visual Perception Sensing;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The presented approach was focused around building intelligence for mobile robot navigation. That was achieved by creating navigation intelligence capabilities while the robot is in motion. The adopted learning paradigm was a five layers Neuro-Fuzzy (NF) learning architecture, due to ability to create and inference for enhanced navigation. To meet such visual data gathering, the mobile robot platform have fully computer-interfaced stereo vision, and reliable 3D perception. Mobile robot intelligence (NF), hence learns navigation (SLAM) maps visual features, as it travels within spaces. Blinding intelligence with visual maps has resulted in better navigation capabilities.

引用

页码：132 / 137

页数：6

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