Indoor fixed-point hovering control for UAVs based on visual inertial SLAM

Abstract

Purpose

Autonomous flight of unmanned aerial vehicles (UAVs) in global position system (GPS)-denied environments has become an increasing research hotspot. This paper aims to realize the indoor fixed-point hovering control and autonomous flight for UAVs based on visual inertial simultaneous localization and mapping (SLAM) and sensor fusion algorithm based on extended Kalman filter.

Design/methodology/approach

The fundamental of the proposed method is using visual inertial SLAM to estimate the position information of the UAV and position-speed double-loop controller to control the UAV. The motion and observation models of the UAV and the fusion algorithm are given. Finally, experiments are performed to test the proposed algorithms.

Findings

A position-speed double-loop controller is proposed, by fusing the position information obtained by visual inertial SLAM with the data of airborne sensors. The experiment results of the indoor fixed-points hovering show that UAV flight control can be realized based on visual inertial SLAM in the absence of GPS.

Originality/value

A position-speed double-loop controller for UAV is designed and tested, which provides a more stable position estimation and enabled UAV to fly autonomously and hover in GPS-denied environment.

Citation

Li, Z., Li, H., Liu, Y., Jin, L. and Wang, C. (2024), "Indoor fixed-point hovering control for UAVs based on visual inertial SLAM", Robotic Intelligence and Automation, Vol. 44 No. 5, pp. 648-657. https://doi.org/10.1108/RIA-06-2023-0081