Localization of Unmanned Aircraft Systems Using Bio-Inspired Algorithms: An Experimental Study

Abstract

This article describes the integrated application of the bio-inspired optimization algorithm LBBA and Digital Compass to enhance the localization of drones in autonomous missions. The work presents a approach covering Airworthiness, Localization and Sensor Fusion. The LBBA algorithm, using data from a LIDAR sensor and information from a Digital Compass, shows significant advances in the safety and effectiveness of autonomous operations on mobile bases. Now, the proposal is to use this advantage to assist in locating drones on a known map. This study contributes to the continuous evolution of autonomous drone technology, promoting a more effective and secure integration of these systems in laboratory testing environments. The results suggest that the combination of 2D localization from a ground robot with interaction with an aerial one offers a robust and reliable solution for the precise localization of drones, paving the way for future innovations in the field of unmanned aerial vehicles.