@inproceedings{593d414529ce4a0ba8fd97724aa02cb7,
title = "Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment",
abstract = "The paper presents an autonomous vision-based guidance and mapping algorithm for navigation of drones in a GPS-denied environment. We propose a novel algorithm that accurately uses OpenCV ArUco markers as a reference for path detection and guidance using a stereo camera. It enables the drone to navigate and map an environment using vision-based path planning. Special attention has been given towards the robustness of guidance and controlling strategy, accuracy in the vehicle pose estimation and real-time operation. The proposed algorithm is evaluated in a 3D simulated environment using ROS and Gazebo. The results have been presented for drone navigation in a maze pattern indoor scenario. Evaluation of the given guidance system in the simulated environment suggests that the proposed system can be used for generating a 2D/3D occupancy grid map autonomously without the use of high-level algorithms and expensive sensors such as lidars.",
keywords = "Gazebo, Pose estimation, Quadcopter, ROS, SLAM, Vision Guidance",
author = "Mahammad Irfan and Sagar Dalai and Kaushal Kishore and Samarth Singh and Akbar, {S. A.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020 ; Conference date: 01-07-2020 Through 03-07-2020",
year = "2020",
month = jul,
doi = "10.1109/ICCCNT49239.2020.9225398",
language = "English",
series = "2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020",
}