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Vincent Havyarimana,Zhu Xiao,Dong Wang 한국전자통신연구원 2016 ETRI Journal Vol.38 No.3
To improve the ability to determine a vehicle’s movement information even in a challenging environment, a hybrid approach called non-Gaussian square root-unscented particle filtering (nGSR-UPF) is presented. This approach combines a square root-unscented Kalman filter (SR-UKF) and a particle filter (PF) to determinate the vehicle state where measurement noises are taken as a finite Gaussian kernel mixture and are approximated using a sparse Gaussian kernel density estimation method. During an outage-free GPS period, the updated mean and covariance, computed using SR-UKF, are estimated based on a GPS observation update. During a complete GPS outage, nGSR-UPF operates in prediction mode. Indeed, because the inertial sensors used suffer from a large drift in this case, SR-UKF-based importance density is then responsible for shifting the weighted particles toward the high-likelihood regions to improve the accuracy of the vehicle state. The proposed method is compared with some existing estimation methods and the experiment results prove that nGSR-UPF is the most accurate during both outage-free and complete-outage GPS periods.
Wonkeun Youn,고하윤,Hyungsik Choi,Inho Choi,Joong-Hwan Baek,Hyun Myung 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
This paper proposes a novel complete navigation system for autonomous flight of small unmanned aerial vehicles (UAVs) in GPS-denied environments. The hardware platform used to test the proposed algorithm is a small, custom-built UAV platform equipped with an onboard computer, RGB-D camera, 2D light detection and ranging (LiDAR), and altimeter. The error-state Kalman filter (ESKF) based on the dynamic model for low-cost IMU-driven systems is proposed, and visual odometry from the RGB-D camera and height measurement from the altimeter are fed into the measurement update process of the ESKF. The pose output of the ESKF is then integrated into the open-source simultaneous location and mapping (SLAM) algorithm for pose-graph optimization and loop closing. In addition, the computationally efficient collision-free path planning algorithm is proposed and verified through simulations. The software modules run onboard in real time with limited onboard computational capability. The indoor flight experiment demonstrates that the proposed system for small UAVs with low-cost devices can navigate without collision in fully autonomous missions while establishing accurate surrounding maps.
상태변수 오차기반 스무더를 이용한 자율이동체 자세오차 보상
김선영(Sun Young Kim),강창호(Chang Ho Kang),송진우(Jin Woo Song) 제어로봇시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.11
In this study, the navigation information of a guided missile was calculated using a smoothing algorithm and used for improving the attitude estimation accuracy of the guided missile. The state variables of the backward filter, designed in the fixed interval smoother, were set to attitude errors in the same way as the forward filter of the fixed interval smoother, which was implemented as a linearized Kalman filter algorithm. To verify the performance of the proposed algorithm, simple guided missile simulations were performed, which confirmed that the attitude error of the guided missile was reduced when the fixed interval smoother was applied.
Lateral Mode Controller Design for Insect-like Tailless Flapping-Wing Micro Air Vehicle
Steven Aurecianus,Hoang Vu Phan,Jungkeun Park(박정근),Hoon Cheol Park(박훈철),Taesam Kang(강태삼) 제어로봇시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.1
In this study, proposed is a PD (Proportional-Derivative) controller for the roll and yaw motions based on the linearized and non-coupled lateral mode dynamic model of the flapping-wing micro air vehicle (FW-MAV) called KUBeetle. First, the lateral mode dynamics model is cascaded with the dynamics of the sensors, filters, and servos to obtain more accurate dynamic model. Then, the stability and robustness of the closed loop control system is analyzed using root locus and H∞ norm stability criteria. From the analyses, the robustly stabilizing PD control gains are determined. It Is found that the simple PD controller of roll motion has big overshoot and large steady error, even though the closed loop system is very stable. To improve the roll controller performance, a loop shaping compensator is designed and cascaded to the proportional feedback part of the roll control loop. It is shown that the complex compensator improves the roll response, and it does not affect much the closed loop stability robustness of the roll control loop. The real flight test was done to check the performance of the proposed control loop and it shows that lateral motion follows the reference command very well as in the simulation.