Enhancing Exploration Algorithms for Navigation with Visual SLAM

被引：4

作者：

Muravyev, Kirill ^{[1
,2
]}

Bokovoy, Andrey ^{[1
]}

Yakovlev, Konstantin ^{[1
]}

机构：

[1] Russian Acad Sci, Fed Res Ctr Comp Sci & Control, Artificial Intelligence Res Inst, Moscow, Russia

[2] Moscow Inst Phys & Technol, Dolgoprudnyi, Russia

来源：

ARTIFICIAL INTELLIGENCE, RCAI 2021 | 2021年 / 12948卷

关键词：

Exploration; Vision-based simultaneous localization and mapping; Simulation; Robotics; VISION; SYSTEM; SCALE; IMU;

D O I：

10.1007/978-3-030-86855-0_14

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Exploration is an important step in autonomous navigation of robotic systems. In this paper we introduce a series of enhancements for exploration algorithms in order to use them with vision-based simultaneous localization and mapping (vSLAM) methods. We evaluate developed approaches in photo-realistic simulator in two modes: with ground-truth depths and neural network reconstructed depth maps as vSLAM input. We evaluate standard metrics in order to estimate exploration coverage.

引用

页码：197 / 212

页数：16

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