A Unmanned Aerial Vehicle (UAV)/Unmanned Ground Vehicle (UGV) Dynamic Autonomous Docking Scheme in GPS-Denied Environments

This study designs a navigation and landing scheme for an unmanned aerial vehicle (UAV) to autonomously land on an arbitrarily moving unmanned ground vehicle (UGV) in GPS-denied environments based on vision, ultra-wideband (UWB) and system information. In the approaching phase, an effective multi-innovation forgetting gradient (MIFG) algorithm is proposed to estimate the position of the UAV relative to the target using historical data (estimated distance and relative displacement measurements). Using these estimates, a saturated proportional navigation controller is developed, by which the UAV can approach the target, making the UGV enter the field of view (FOV) of the camera deployed in the UAV. Then, a sensor fusion estimation algorithm based on an extended Kalman filter (EKF) is proposed to achieve accurate landing. Finally, a numerical example and a real experiment are used to support the theoretical results.

Automated summary

This study proposes a navigation and landing scheme for UAVs to autonomously land on moving UGVs in GPS-denied environments using vision, UWB, and system information. The position estimation of the UAV relative to the target is performed using a multi-innovation forgetting gradient algorithm. A proportional navigation controller is developed for approaching the target and a sensor fusion estimation algorithm based on EKF is used for accurate landing.