• Title/Summary/Keyword: Yaw error

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Adaptive Sliding Mode Control based on Feedback Linearization for Quadrotor with Ground Effect

  • Kim, Young-Min;Baek, Woon-Bo
    • Journal of Advanced Information Technology and Convergence
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    • v.8 no.2
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    • pp.101-110
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    • 2018
  • This paper introduces feedback linearization (FL) based adaptive sliding mode control (ASMC) effective against ground effects of the quadrotor UAV. The proposed control has the capability of estimation and effective rejection of those effects by adaptive mechanism, which resulting stable attitude and positioning of the quadrotor. As output variables of quadrotor, x-y-z position and yaw angle are chosen. Dynamic extension of the quadrotor dynamics is obtained for terms of roll and pitch control input to be appeared explicitly in x-y-z dynamics, and then linear feedback control including a ground effect is designed. A sliding mode control (SMC) is designed with a class of FL including higher derivative terms, sliding surfaces for which is designed as a class of integral type of resulting closed loop dynamics. The asymptotic stability of the overall system was assured, based on Lyapunov stability methods. It was evaluated through some simulation that attitude control capability is stable under excessive estimation error for unknown ground effect and initial attitude of roll, pitch, and yaw angle of $30^{\circ}$ in all. Effectiveness of the proposed method was shown for quadrotor system with ground effects.

Optimal design of a flexure hinge-based XY AFM scanner for minimizing Abbe errors and the evaluation of pitch measuring uncertainty of a nano-accuracy AFM system (XY 스캐너의 아베 오차 최소화를 위한 최적 설계 및 나노 정밀도의 원자 현미경 피치 측정 불확도 평가)

  • Kim Dong-Min;Lee Dong-Yeon;Gweon Dae-Gab
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.6 s.183
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    • pp.96-103
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    • 2006
  • To establish of standard technique of nano-length measurement in 2D plane, new AFM system has been designed. In the long range (about several tens of ${\mu}m$), measurement uncertainty is dominantly affected by the Abbe error of XY scanning stage. No linear stage is perfectly straight; in other words, every scanning stage is subject to tilting, pitch and yaw motion. In this paper, an AFM system with minimum offset of XY sensing is designed. And XY scanning stage is designed to minimize rotation angle because Abbe errors occur through the multiply of offset and rotation angle. To minimize the rotation angle optimal design has performed by maximizing the stiffness ratio of motion direction to the parasitic motion direction of each stage. This paper describes the design scheme of full AFM system, especially about XY stage. Full range of fabricated XY scanner is $100{\mu}m\times100{\mu}m$. And tilting, pitch and yaw motion are measured by autocollimator to evaluate the performance of XY stage. As a result, XY scanner can have good performance. Using this AFM system, 3um pitch specimen was measured. The uncertainty of total system has been evaluated. X and Y direction performance is different. X-direction measuring performance is better. So to evaluate only ID pitch length, X-direction scanning is preferable. Its expanded uncertainty(k=2) is $\sqrt{(3.96)^2+(4.10\times10^{-5}{\times}p)^2}$ measured length in nm.

Measurement of Construction Material Quantity through Analyzing Images Acquired by Drone And Data Augmentation (드론 영상 분석과 자료 증가 방법을 통한 건설 자재 수량 측정)

  • Moon, Ji-Hwan;Song, Nu-Lee;Choi, Jae-Gab;Park, Jin-Ho;Kim, Gye-Young
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.1
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    • pp.33-38
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    • 2020
  • This paper proposes a technique for counting construction materials by analyzing an image acquired by a Drone. The proposed technique use drone log which includes drone and camera information, RCNN for predicting construction material type, dummy area and Photogrammetry for counting the number of construction material. The existing research has large error ranges for predicting construction material detection and material dummy area, because of a lack of training data. To reduce the error ranges and improve prediction stability, this paper increases the training data with a method of data augmentation, but only uses rotated training data for data augmentation to prevent overfitting of the training model. For the quantity calculation, we use a drone log containing drones and camera information such as Yaw and FOV, RCNN model to find the pile of building materials in the image and to predict the type. And we synthesize all the information and apply it to the formula suggested in the paper to calculate the actual quantity of material pile. The superiority of the proposed method is demonstrated through experiments.

A quantitative analysis of synthetic aperture sonar image distortion according to sonar platform motion parameters (소나 플랫폼의 운동 파라미터에 따른 합성개구소나 영상 왜곡의 정량적 분석)

  • Kim, Sea-Moon;Byun, Sung-Hoon
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.4
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    • pp.382-390
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    • 2021
  • Synthetic aperture sonars as well as side scan sonars or multibeam echo sounders have been commercialized and are widely used for seafloor imaging. In Korea related research such as the development of a towed synthetic aperture sonar system is underway. In order to obtain high-resolution synthetic aperture sonar images, it is necessary to accurately estimate the platform motion on which it is installed, and a precise underwater navigation system is required. In this paper we are going to provide reference data for determining the required navigation accuracy and precision of navigation sensors by quantitatively analyzing how much distortion of the sonar images occurs according to motion characteristics of the platform equipped with the synthetic aperture sonar. Five types of motions are considered and normalized root mean square error is defined for quantitative analysis. Simulation for error analysis with parameter variation of motion characteristics results in that yaw and sway motion causes the largest image distortion whereas the effect of pitch and heave motion is not significant.

A Study on an Integral State Feedback Controller for Way-point Tracking of an AUV (무인잠수정의 적분 상태 궤환 제어기 설계 및 경유점 추적 연구)

  • Bae, Seol B.;Shin, Dong H.;Park, Sang H.;Joo, Moon G.
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.8
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    • pp.661-666
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    • 2013
  • A state feedback controller with integration of output error is proposed for way-point tracking of an AUV (Autonomous Underwater Vehicle). For the steering control on the XY plane, the proposed controller uses three state variables (sway velocity, yaw rate, heading angle) and the integral of the steering error, and for the depth control on the XZ plane, it uses four state variables (pitch rate, depth, pitch angle) and the integral of the depth error. From the simulation using Matlab/Simulink, we verify that the performance of the proposed controller is satisfactory within an error range of 1m from the target way-point for arbitrarily chosen sets of consecutive way-points.

3D Multi-floor Precision Mapping and Localization for Indoor Autonomous Robots (실내 자율주행 로봇을 위한 3차원 다층 정밀 지도 구축 및 위치 추정 알고리즘)

  • Kang, Gyuree;Lee, Daegyu;Shim, Hyunchul
    • The Journal of Korea Robotics Society
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    • v.17 no.1
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    • pp.25-31
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    • 2022
  • Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

Path-following Control for Autonomous Navigation of Marine Vessels Considering Disturbances (외력을 고려한 선박의 자율운항을 위한 경로추종 제어)

  • Lee, Sang-Do
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.5
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    • pp.557-565
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    • 2021
  • Path-following control is considered as one of the most fundamental skills to realize autonomous navigation of marine vessels in the ocean. This study addresses with the path-following control for a ship in which there are environmental disturbances in the directions of the surge, sway, and yaw motions. The guiding principle and back-stepping method was utilized to solve the ship's tracking problem on the reference path generated by a virtual ship. For path-following control, error dynamics is one of the most important skills, and it extends to the research fields of automatic collision avoidance and automatic berthing control. The algorithms for the guiding principles and error variables have been verified by numerical simulation. As a result, most error variables converged to zero values with the controller except for the yaw angle error. One of the most interesting results is that the tracking errors of path-following control between two ships are smaller than the existing safe passing distances considering interaction forces from near passing ships. Moreover, a trade-off between tracking performance and the ship's safety should be considered for determining the proper control parameters to prevent the destructive failure of actuators such as propellers, fins, and rudders during the path-following of marine vessels.

A Model-based 3-D Pose Estimation Method from Line Correspondences of Polyhedral Objects

  • Kang, Dong-Joong;Ha, Jong-Eun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.762-766
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    • 2003
  • In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

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Development and Validation of A Finite Optimal Preview Control-based Human Driver Steering Model (최적예견 제어 기법을 이용한 운전자 조향 모델의 개발 및 검증)

  • Kang, Ju-Yong;Yi, Kyong-Su;Noh, Ki-Han
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.855-860
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    • 2007
  • This paper describes a human driver model developed based on finite preview optimal control method. The human driver steering model is constructed to minimize a performance index which is a quadratic form of lateral position error, yaw angle error and steering input. Simulation studies are conducted using a vehicle simulation software, Carsim. The Carsim vehicle model is validated using vehicle test data. In order to validate the human driving steering model, the human driver steering model is compared to the driving data on a virtual test track(VTT) and the actual vehicle test data. It is shown that human driver steering behaviors can be well represented by the human driver steering model presented in this paper

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Development of an Intelligent Autonomous Control Algorithm and Test Vehicle Performance Verification (지능형 자율주행 제어 알고리즘 개발 및 시험차량 성능평가)

  • Kim, Won-Gun;Yi, Kyong-Su
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.861-866
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    • 2007
  • This paper presents development of a vehicle lateral and longitudinal control for autonomous driving control and test results obtained using an electric vehicle. Sliding control theory has been used to develop a vehicle speed and distance control algorithm. The longitudinal control algorithm that maintains safety and comfort of the vehicle consists of a cruise and STOP&GO control depending on traffic conditions. Desired steering angle is determined through the lateral position error and the yaw angle error based on preview optimal control. Motor control inputs have been directly derived from the sliding control law. The performance of the autonomous driving control which is integrated with a lateral and longitudinal control is investigated by computer simulations and driving test using an electric vehicle. Electric vehicle system consists of DC driving motor, an electric power steering system, main controller (Autobox)

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