@inproceedings{f6e28d847a0f4bbfadbe0c261c06dd99,
title = "Point of Interest Mode for Indoor Drone Based on Feature Matching",
abstract = "In autonomous navigation systems, point of interest (POI) technology has been extensively utilized in outdoor drones as a smart flight mode, enabling them to quickly orbit interesting locations and gather comprehensive data with a 360-degree view of the target. In indoor environments, POIs are crucial for addressing GPS (Global Positioning System) signal disruptions caused by building structures. In this paper, we propose an indoor drone capable of intelligent flight based on visual sensing from an onboard camera. A 3D (3 Dimention) object serves as a reference to determine the drone's target point. We adopt the ORB algorithm due to its advantages in real-time processing. Our results demonstrate consistent accuracy in feature point matching and robust performance against noise, leading to more stable feature extraction.",
keywords = "ORB, Point of Interest, camera, drone, feature matching, object, position tracking",
author = "Swista, \{Maharani Wisudawati\} and Ronny Mardiyanto and Rudy Dikairono",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 7th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2024 ; Conference date: 11-12-2024",
year = "2024",
doi = "10.1109/ISRITI64779.2024.10963381",
language = "English",
series = "7th International Seminar on Research of Information Technology and Intelligent Systems: Advanced Intelligent Systems in Contemporary Society, ISRITI 2024 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "795--799",
editor = "Wibowo, \{Ferry Wahyu\}",
booktitle = "7th International Seminar on Research of Information Technology and Intelligent Systems",
address = "United States",
}