UWB-IMU 멀티 모델 알고리즘을 통한 무인 비행체의 실내 위치 인식

Abstract

In this article, we described about the UWB-IMU integrated system for indoor pose estimation of unmanned aerial vehicles (UAVs). Based on the extended Kalman filter (EKF) algorithm, the pose of the UAV and position of UWB anchors can be estimated, but it can only approximate a uni-modal probability distribution function. To estimate the UAV’s two dynamic models (linear motion and rotation) properly, we propose a multi-modal algorithm which is calculating weighted sum of Gaussians of two different states. We simulated this algorithm with indoor motion tracking system.