Autonomous Aerial Refueling for UAVs Based on GPS/MV

Abstract:

According to the UAV autonomous aerial refueling based on GPS/Machine Vision integration, the restrictions on the sensors during docking are analyzed. An adaptive Federal Kalman Filter (AFKF) is proposed, which is based on extended Kalman filter arithmetic, after modeling the sensors measurement models. Reference trajectory of docking is planed using cubic interpolators and docking control laws are designed with LQR. Simulation results show that the controller ensure the stabilized tracking and docking, and the AFKF outputs is continuous and stabilized during sensor failure comparing to centralize Kalman filter.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 4087-4094
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.4087
• Online since: January 2012
• Authors: Long Wang, Xin Min Dong, Jun Guo, Hai Yan Jia
• Keywords: Autonomous Aerial Refueling, Federal Filter, LQR, Machine Vision, Sensor Fusion

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