Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment

Irfan, M and Dalai, S and Kishore, K and Singh, S and Akbar, SA (2020) Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment. In: 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT-2020), July 1-3, 2020, IIT Kharagpur, India.

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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.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	ROS, Gazebo, Pose estimation, Quadcopter, Vision guidance, SLAM.
Subjects:	Electronic Systems > Digital Systems
Divisions:	Electronic Systems
Depositing User:	Mr. Jitendra Nath Bajpai
Date Deposited:	10 Sep 2021 11:27
Last Modified:	10 Sep 2021 11:27
URI:	http://ceeri.csircentral.net/id/eprint/554

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