Improvement in the UAV position estimation with low-cost GPS, INS and vision-based system: Application to a quadrotor UAV
This work addresses the need for accurate UAV position estimation using affordable sensors, offering a practical improvement for low-cost drones.
The paper develops a position estimation system for UAVs using low-cost GPS, INS, and vision-based optical flow, achieving improved accuracy over conventional GPS-INS fusion in hovering and trajectory tracking tests.
In this paper, we develop a position estimation system for Unmanned Aerial Vehicles formed by hardware and software. It is based on low-cost devices: GPS, commercial autopilot sensors and dense optical flow algorithm implemented in an onboard microcomputer. Comparative tests were conducted using our approach and the conventional one, where only fusion of GPS and inertial sensors are used. Experiments were conducted using a quadrotor in two flying modes: hovering and trajectory tracking in outdoor environments. Results demonstrate the effectiveness of the proposed approach in comparison with the conventional approaches presented in the vast majority of commercial drones.