Improving Visual SLAM by Combining SVO and ORB-SLAM2 with a Complementary Filter to Enhance Indoor Mini-Drone Localization under Varying Conditions

被引：5

作者：

Basiri, Amin ^{[1
]}

Mariani, Valerio ^{[2
]}

Glielmo, Luigi ^{[3
]}

机构：

[1] Univ Sannio Benevento, Dept Engn, Piazza Roma 21, Via Traiano, 3, BN, I-82100 Benevento, Italy

[2] ENEA, Dept Energy Technol & Renewable Energy Sources, I-80055 Portici, NA, Italy

[3] Univ Naples Federico II, Dept Elect Engn & Informat Technol, Cso Umberto I, 40, I-80138 Naples, NA, Italy

来源：

DRONES | 2023年 / 7卷 / 06期

关键词：

visual SLAM; indoor positioning; mini-drone;

D O I：

10.3390/drones7060404

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

Mini-drones can be used for a variety of tasks, ranging from weather monitoring to package delivery, search and rescue, and also recreation. In outdoor scenarios, they leverage Global Positioning Systems (GPS) and/or similar systems for localization in order to preserve safety and performance. In indoor scenarios, technologies such as Visual Simultaneous Localization and Mapping (V-SLAM) are used instead. However, more advancements are still required for mini-drone navigation applications, especially in the case of stricter safety requirements. In this research, a novel method for enhancing indoor mini-drone localization performance is proposed. By merging Oriented Rotated Brief SLAM (ORB-SLAM2) and Semi-Direct Monocular Visual Odometry (SVO) via an Adaptive Complementary Filter (ACF), the proposed strategy achieves better position estimates under various conditions (low light in low-surface-texture environments and high flying speed), showing an average percentage error of 18.1% and 25.9% smaller than that of ORB-SLAM and SVO against the ground-truth.

引用

页数：21