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

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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.
Publisher
한국로봇학회
Issue Date
2020-08-17
Language
Korean
Citation

제 15회 한국로봇종합학술대회 (KRoC 2020), pp.11 - 13

URI
http://hdl.handle.net/10203/277826
Appears in Collection
EE-Conference Papers(학술회의논문)
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