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A Position and Velocity Estimation Using Multifarious and Multiple Sensor Fusion
Youngwan Cho,Heejin Lee 한국지능시스템학회 2017 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.17 No.2
In this paper, we propose a fusion algorithm of multifarious and multiple sensors to enhance the accuracy and reliability of position and velocity estimation for the vehicles. We proposed an adaptive Kalman filter for multiple sensor fusion to provide a fault tolerant estimation. We verified the multiple sensor fusion estimator can provide a fault tolerant estimation through Matlab simulation and laboratory equipped experiments. We also proposed a fusion algorithm of multifarious sensors in order to enhance the velocity estimation accuracy. We proposed a Kalman filter error correction for compensate the accumulative error in the main sensor with the other type of sensor which has characteristic of biased error. We also developed a fusion algorithm for compensate the error in the position measuring with the velocity measuring. We made experiments for estimating position and velocity of vehicle simultaneously through the fusion of multifarious and multiple sensors and showed that average position error was 1.5764 m and average velocity accuracy was 99.81%.
A Study on EKF-SLAM Simulation of Autonomous Flight Control of Quadcopter
Youngwan Cho,Jae-young Hwang 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.9
In the field of autonomous navigation control of unmanned vehicles, it is most essential to estimate the location of the controlled vehicle. In this paper, a method for estimating the location of a quadcopter is proposed to autonomously control the flight of an unmanned quadcopter. The algorithm for estimating the location of a quadcopter is proposed by applying the EKF-SLAM, and the algorithm is simulated for the system to estimate and control the flight trajectories of the quadcopter. Prior to simulation, a dynamic model for the quadcopter is introduced, and simulations are carried out to determine the manner in which the quadcopter changes with respect to the thrust. Moreover, the leveling control and posture control are simulated through a PD controller, and the flight trajectories of the quadcopter are analyzed through the posture control. Furthermore, a virtual landmark is established for applying the EKF-SLAM based on a fabricated quadcopter simulator. Moreover, an observation model for observing the landmark is proposed for estimating the flight trajectories of the quadcopter, along with a state equation and a Jacobian matrix. Finally, potential advancement in the simultaneous location estimation and mapping technology of the quadcopter is presented by simulating the quadcopter EKF-SLAM and validating its performance.
Youngwan Cho,Haemin Woo,Seungwoo Kim,Minkee Park 대한전자공학회 2009 ITC-CSCC :International Technical Conference on Ci Vol.2009 No.7
This paper presents a 3 dimensional visual simulation approach for automated cruise control system with collision avoidance in multi-vehicle traffics environment. The longitudinal and lateral directions of the autonomous vehicle are determined from higher level fuzzy neural network control scheme imitating human behavior. The motion of the controlled vehicle is simulated together with the vehicles cruising predetermined path under 3D modeled simulation environment.
Building a HOG Descriptor Model of Pedestrian Images Using GA and GP Learning
Cho, Youngwan,Seo, Kisung Korean Institute of Intelligent Systems 2018 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.18 No.2
For detecting a pedestrian by using features of images, it is generally needed to establish a reference model that is used to match with input images. The support vector machine (SVM) or AdaBoost Cascade method have been generally used to train the reference pedestrian model in the approaches using the histogram of oriented gradients (HOG) as features of the pedestrian model. In this paper, we propose a new approach to match HOG features of input images with reference model and to learn the structure and parameters of the reference model. The Gaussian scoring method proposed in this paper evaluates the degree of feature coincidence with HOG maps divided with angle of the HOG vector. We also propose two approaches for leaning of the reference model: genetic algorithm (GA) based learning and genetic programming (GP) based learning. The GA and GP are used to search the best parameters of the gene and nonlinear function representing feature map of pedestrian model, respectively. We performed experiments to verify the performance of proposed method in terms of accuracy and processing time with INRIA person dataset.
Building a HOG Descriptor Model of Pedestrian Images Using GA and GP Learning
Youngwan Cho,Kisung Seo 한국지능시스템학회 2018 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.18 No.2
For detecting a pedestrian by using features of images, it is generally needed to establish a reference model that is used to match with input images. The support vector machine (SVM) or AdaBoost Cascade method have been generally used to train the reference pedestrian model in the approaches using the histogram of oriented gradients (HOG) as features of the pedestrian model. In this paper, we propose a new approach to match HOG features of input images with reference model and to learn the structure and parameters of the reference model. The Gaussian scoring method proposed in this paper evaluates the degree of feature coincidence with HOG maps divided with angle of the HOG vector. We also propose two approaches for leaning of the reference model: genetic algorithm (GA) based learning and genetic programming (GP) based learning. The GA and GP are used to search the best parameters of the gene and nonlinear function representing feature map of pedestrian model, respectively. We performed experiments to verify the performance of proposed method in terms of accuracy and processing time with INRIA person dataset.
쿼드로터 자세 안정화를 위한 센서융합 기반 3중 중첩 PID 제어기
조영완(Youngwan Cho) 대한전기학회 2018 전기학회논문지 Vol.67 No.7
In this paper, we propose a triple nested PID control scheme for stable hovering of a quadrotor and propose a complementary filter based sensor fusion technique to improve the performance of attitude, altitude and velocity measurement. The triple nested controller has a structure in which a double nested attitude controller that has the angular velocity PD controller in inner loop and the angular PI controller in outer loop, is nested in a velocity control loop to enable stable hovering even in the case of disturbance. We also propose a sensor fusion technique by applying a complementary filter in order to reduce the noise and drift error included in the acceleration and gyro sensor and to measure the velocity by fusing image, gyro, and acceleration sensor. In order to verity the performance, we applied the proposed control and measurement scheme to hovering control of quadrotor.
Assessment of Wear Characteristics of Paper-Based Wet Friction Materials
Cho, Hak-Rae,Je, Youngwan,Chung, Koo-Hyun Korean Society for Precision Engineering 2018 International Journal of Precision Engineering and Vol.19 No.5
A wet clutch synchronizes the speed and transmits power from an engine or motor to a drive train by mechanical coupling between a friction disk and a separate disk. The performance of a wet clutch may be significantly dependent on the friction and wear characteristics of paper-based friction materials. In this work, the wear characteristics of paper-based friction materials were experimentally investigated using a pin on reciprocating plate tribo-tester. In particular, the wear characteristics of paper-based friction materials with and without carbon fibers were assessed in a boundary lubrication state with respect to normal force and sliding speed. The tests found that the wear rate of paper-based friction materials increased with increasing normal force and sliding speed. The wear rates were found to vary in the range of <TEX>$10^{-6}-10^{-4}mm^3/(N{\cdot}cycle)$</TEX>. In addition, paper-based friction material with carbon fiber exhibited relatively larger friction and wear characteristics than those without carbon fibers. It was observed that the carbon fibers were broken due to the sliding contact, which may have contributed to the wear progression. The outcomes of this work may be helpful in gaining a better understanding of the tribological characteristics of paper-based friction materials in order to enhance the lifetimes of wet clutches.