İHA'ların İç Mekan Otonom Navigasyonu için ORB-SLAM Tabanlı 2D Ortamın Yeniden Yapılandırılması

Year 2020, Ejosat Special Issue 2020 (ICCEES), 466 - 472, 05.10.2020

Abdullah Yusefı , Akif Durdu , Cemil Sungur

https://doi.org/10.31590/ejosat.819620

Cited By: 2

Abstract

Bu yazıda, insansız hava araçları için basit ve ekonomik ancak verimli bir otonom haritalama ve navigasyon sistemi sunulmaktadır. Bu sistemi gerçekleştirmek için üç modül uygulanmıştır. İlk modül, dronda otonom olarak gezinirken ortamın 3 boyutlu bir modelini oluşturur ve ORB-SLAM adı verilen en iyi monoküler SLAM algoritmalarından birine dayanır. Sistemin otonom navigasyonu için görsel tabanlı bir hat izleme yöntemi önerilmiştir. Daha sonra, ikinci modül, 3 boyutlu haritanın 2 boyutlu ızgara haritasına gerçek zamanlı dönüşümünü gerçekleştirir. 3B'den 2B'ye harita dönüştürme çalışmalarının çoğu, ikisinin ortasında oktomaplar kullanırken, herhangi bir orta bileşene ihtiyaç duymadan 3B haritayı doğrudan 2B'ye dönüştüren eşik tabanlı bir yöntem sunuyoruz. Son olarak, üçüncü modül, dronu yapılandırılmış 2B ızgara haritasında hedef pozuna götürmek için A* yol planlama algoritmasını kullanır. Bu modül, bu görevi tamamlamak için monoküler kamera bilgileriyle birlikte yalnızca IMU destekli Uyarlanabilir Monte Carlo Konumlandırmasını(AMCL) kullanır. Deney sonuçları, önerilen sistemin yalnızca monoküler bir kamera ve üzerinde sınırlı işlem kaynakları bulunan düşük maliyetli drone'larda kullanılmak için yeterince verimli olduğunu göstermektedir.

Keywords

ORB-SLAM, Hat İzleme, Harita Dönüştürme, AMCL, Otonom Navigasyon

ORB-SLAM-based 2D Reconstruction of Environment for Indoor Autonomous Navigation of UAVs

Abstract

In this paper, a simple and economic yet efficient autonomous mapping and navigation system for unmanned aerial vehicles is presented. In order to realize this system, three modules have been implemented. First module constructs a 3D model of the environment while autonomously navigating the drone and is based on one of the top monocular SLAM algorithms called ORB-SLAM. For the autonomous navigation of the system a visual-based line tracking method is proposed. Afterwards, the second module performs a real time transformation of the 3D map to 2D grid map. While most of the 3D to 2D map conversion studies use octomaps in the middle of two, we present a threshold-based method that directly converts the 3D map to 2D without need for any middle component. Finally, third module uses A* path planning algorithm to navigate the drone to the goal pose in the constructed 2D grid map. This module uses only IMU-aided Adaptive Monte Carlo localization (AMCL) combined with monocular camera information to complete this task. The experimentation results indicate that the proposed system is adequately efficient to be used in the low-cost drones that have only a monocular camera and limited processing resources on them.

Keywords

ORB-SLAM, Line-Tracking, Map Conversion, AMCL, Autonomous Navigation

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