Mobile Robot Vision Navigation & Localization Using Gist and Saliency

被引：50

作者：

Chang, Chin-Kai ^{[1
]}

Siagian, Christian ^{[1
]}

Itti, Laurent ^{[2
]}

机构：

[1] Univ Southern Calif, Dept Comp Sci, Hedco Neurosci Bldg,Room 10,3641 Watt Way, Los Angeles, CA 90089 USA

[2] Univ Southern Calif, Fac Comp Sci Psychol & Neurosci, Los Angeles, CA 90089 USA

来源：

IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010) | 2010年

关键词：

FEATURES;

D O I：

10.1109/IROS.2010.5649136

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a vision-based navigation and localization system using two biologically-inspired scene understanding models which. are studied from human visual capabilities: (1) Gist model which captures the holistic characteristics and layout of an image and (2) Saliency model which emulates the visual attention of primates to identify conspicuous regions in the Image. Here the localization system utilizes the gist features and salient regions to accurately localize the robot while the navigation system uses the salient regions to perform visual feedback control to direct its heading and go to a user-provided goal location. We tested the system on our robot, Beobot2.0, in an indoor and outdoor environment with a route length of 36.67 m (10,890 video frames) and 138.27m (28,971 frames), respectively. On average, the robot is able to drive within 3.68cm and 8.78cm (respectively) of the center of the lane.

引用

页码：4147 / 4154

页数：8