ArUco Marker-Based autonomous UAV navigation for reconnaissance operations in urban terrain environments

Cahya Pradika; Imanuel Dindin; Erzi Agson Gani; Ardan Nagra Coutsar; Mochamad Riza Pratama

doi:10.21831/jamat.v3i1.3018

Authors

Cahya Pradika Universitas Pertahanan, Indonesia
Imanuel Dindin Universitas Pertahanan, Indonesia
Erzi Agson Gani Universitas Pertahanan, Indonesia
Ardan Nagra Coutsar Universitas Pertahanan, Indonesia
Mochamad Riza Pratama Institut Teknologi Sepuluh Nopember, Indonesia

DOI:

https://doi.org/10.21831/jamat.v3i1.3018

Keywords:

ArUco Maker-Based, Navigation, Unmanned Aerial Vehicle, Reconnaissance Operations

Abstract

This study demonstrated the feasibility of autonomous UAV navigation in GPS-denied indoor environments using ArUco marker-based visual localization integrated with a VL53L1X LiDAR sensor and PX4 Offboard control. The developed system successfully validated markers, performed real-time pose estimation, and navigated sequentially through waypoints without human intervention. The web-based monitoring interface and QGroundControl integration operated reliably throughout all trials, enabling effective dual-platform telemetry monitoring and manual setpoint adjustment from a safe standoff position. The ArUco-marker-based detection, implemented using the OpenCV DICT_5×5_250 dictionary, validated marker identities within a functional altitude range of 40 to 200 cm. Third, across 61 trials discrete movement samples spanning four path configurations—straight-axis, lateral-right, lateral-left, and compound multi-direction—the system achieved an overall navigation success rate of 70%. Navigation failures caused by synchronization lag between UAV translational velocity and the camera’s image processing frame rate, which prevented timely marker validation during high-speed maneuvers. These results confirm that ArUco marker-guided UAV navigation is a viable, low-infrastructure solution for initial indoor reconnaissance in GPS-denied military environments, and establish a quantitative baseline for future enhancements, including precision landing algorithms and dynamic marker placement strategies.

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