Self-positioning for UAV indoor navigation based on 3D laser scanner, UWB and INS

Abstract

In some GPS-denied indoor environment, micro Unmanned Aerial Vehicle (UAV) is a good choice to execute special tasks. However, self-positioning of UAV becomes difficult without the help of GPS. In this paper, we develop the self-positioning method for UAV indoor navigation, which integrates the information of 3D laser scanner, ultra-wideband (UWB) and Inertial navigation system (INS). The positioning model of INS, UWB and 3D laser scanner is analyzed. And then data fusion strategy based on Kalman filtering is introduced to improve the overall localization precision. The method is verified by simulation and the results show that the strategy improves positioning accuracy significantly compared to INS-only and UWB-only approaches.