• 대한기계학회논문집A
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• 제30권6호
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• pp.653-661
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• 2006

Metallic sandwich plates with various inner cores have important new features with not only ultra-light material characteristics and load bearing function but also multifunctional characteristics. Because of production possibility on the large scale and a good geometric precision, sandwich plates with inner dimpled shell structure from a single material have advantages as compared with other solid sandwich plates. Inner dimpled shell structures can be fabricated with press or roll forming process, and then bonded with two face sheets by multi-point resistance welding or adhesive bonding. Elasto-plastic bending behavior of sandwich plates have been predicted analytically and measured. The measurements have shown that elastic perfectly plastic approximation can be conveniently employed with less than 10% error in elastic stiffness, collapse load, and energy absorption. The dominant collapse modes are face buckling and bonding failure after yielding. Sandwich plates with inner dimpled shell structure can absorb more energy than other types of sandwich plates during the bending behavior.

• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.292-304
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• 2005

In this paper we present the linearized equations of motion for a bicycle as a benchmark. The results obtained by pencil-and-paper and two programs are compared. The bicycle model we consider here consists of four rigid bodies, viz. a rear frame, a front frame being the front fork and handlebar assembly, a rear wheel and a front wheel, which are connected by revolute joints. The contact between the knife-edge wheels and the flat level surface is modelled by holonomic constraints in the normal direction and by non-holonomic constraints in the longitudinal and lateral direction. The rider is rigidly attached to the rear frame with hands free from the handlebar. This system has three degrees of freedom, the roll, the steer, and the forward speed. For the benchmark we consider the linearized equations for small perturbations of the upright steady forward motion. The entries of the matrices of these equations form the basis for comparison. Three diffrent kinds of methods to obtain the results are compared : pencil-and-paper, the numeric multibody dynamics program SPACAR, and the symbolic software system Auto Sim. Because the results of the three methods are the same within the machine round-off error, we assume that the results are correct and can be used as a bicycle dynamics benchmark.

• 대한기계학회논문집A
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• 제28권3호
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• pp.230-237
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• 2004

Lane Sensing techniques based on vision sensors are regarded promising because they require little infrastructure on the highway except clear lane markers. However, they require more intelligent processing algorithms in vehicles to generate the previewed roadway from the vision images. In this paper, a lane sensing algorithm using vision sensors is developed to improve the sensing robustness. The parallel stereo-camera is utilized to regenerate the 3-dimensional road geometry. The lane geometry models are derived such that their parameters represent the road curvature, lateral offset and heading angle, respectively. The parameters of the lane geometry models are estimated by the Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from the image plane to the global coordinate considers roll and pitch motions of a vehicle so that the mapping error is minimized during acceleration, braking or steering. The proposed sensing system has been built and implemented on a 1/10-scale model car.

• Journal of Astronomy and Space Sciences
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• 제29권4호
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• pp.389-395
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• 2012

The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

• 로봇학회논문지
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• 제10권4호
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• pp.186-192
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• 2015

This paper proposes a robust balance and driving control for omni-directional ball robot(generally called ball-bot) with two axis mecanum wheel. Slip between ball and mecanum wheel actuator inevitably occurs along diagonal axis due to its instantaneous strong torque. In order to reduce and saturate slip, exact distance calculation scheme especially for rotational movement is essential. So this research solved Euler-Lagrange dynamics for proposed two axis ball robot based on practical mechanical modeling. Robust balance control was carried out by PID controller according to the pitch and roll angles of ball robot by using sensor fusion between AHRS and wheel encoder. Proposed PID controller enhances stability by reducing steady state error and settling time. Proposed slip control algorithm for omni-directional ball robot has been demonstrated by experiments for balance control and arbitrary driving control.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1145-1157
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• 2020

A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.565-573
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• 2017

This paper presents a multistage in-flight alignment (MIFA) method for a strapdown inertial navigation system (SDINS) suitable for moving vehicles with no initial attitude references. A SDINS mounted on a moving vehicle frequently loses attitude information for many reasons, and it makes solving navigation equations impossible because the true motion is coupled with an undefined vehicle attitude. To determine the attitude in such a situation, MIFA consists of three stages: a coarse horizontal attitude, coarse heading, and fine attitude with adaptive Kalman navigation filter (AKNF) in order. In the coarse horizontal alignment, the pitch and roll are coarsely estimated from the second order damping loop with an input of acceleration differences between the SDINS and GPS. To enhance estimation accuracy, the acceleration is smoothed by a scalar filter to reflect the true dynamics of a vehicle, and the effects of the scalar filter gains are analyzed. Then the coarse heading is determined from the GPS tracking angle and yaw increment of the SDINS. The attitude from these two stages is fed back to the initial values of the AKNF. To reduce the estimated bias errors of inertial sensors, special emphasis is given to the timing synchronization effects for the measurement of AKNF. With various real flight tests using an UH60 helicopter, it is proved that MIFA provides a dramatic position error improvement compared to the conventional gyro compass alignment.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.683-688
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• 2009

본 논문에서는 비젼을 이용한 영상처리 기술을 기반으로 비접촉식 미세 측정 광학기에 의해 측정된 이미지를 템플릿 매칭과 B-Spline 보간법에 의해 보다 빠르고, 정밀한 복원 기법을 제안한다. 이를 위해 먼저 각각의 이미지로부터 매칭 템플릿과 피 매칭 템플릿을 검출한다. 그런 다음 기준면으로부터 두 이미지의 중첩되는 부분의 롤, 피치, 요 오차를 보정하여 정합시킨다. 그리고 B-Spline 보간법에 의해 정합된 부분을 연속화한다. 마지막으로, 제안된 방법은 실험을 통해 그 응용 가능성을 증명한다.

• 로봇학회논문지
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• 제14권1호
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• pp.65-73
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• 2019

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

• 대한방사선치료학회지
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• 제29권1호
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• pp.7-18
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• 2017

목 적: 영상유도를 통한 6DoF Couch의 이동 정확성의 검증을 위해 QA Set을 제작하였고, 그 유용성을 평가하였다. 대상 및 방법: 6DoF Couch와 CBCT가 설치된 두 대의 선형가속기를 대상으로 하였으며, 자체 제작한 YCC QA Set을 이용하여 수평수직(Translation; TX, TY, TZ)과 회전(Rotation, Pitch; RX, Roll; RY, Yaw; RZ) 여섯방향의 Off-Set 값이 설정된 Penta-Guide Phantom의 CBCT영상을 각각 15회에 걸쳐 획득하였다. 이를 통해 기준영상(Reference Image)과 보정영상(Registration Image)을 비교하였으며, 보정된 6DoF Couch의 이동정확성을 실측하여 오차를 분석하였다. 결 과: 기준영상과 보정영상의 Air Cavity에 해당하는 Pixel들은 모두 30에서 66 사이에 포함되어 보정정확도가 높게 나타났다. 6DoF Couch의 Off-set의 보정 결과 값과 실측치의 비교에서 수평수직방향의 오차는 TX방향은 $0.25{\pm}.18mm$ TY방향은 $0.25{\pm}.25mm$ TZ방향에서 $0.36{\pm}.2mm$로 나타났다. 그리고 회전방향의 오차는 RX방향은 $0.18{\pm}.08^{\circ}$ RY방향은 $0.26{\pm}.09^{\circ}$ RZ방향에서 $0.11{\pm}.08^{\circ}$로서, 임의의 값에 대하여 정확하게 보정되었다. 결 론: YCC QA Set을 이용해 매우 간단한 방법으로 6DoF Couch의 수평수직방향뿐 아니라 회전방향의 오차에 대한 검증을 할 수 있었으며, 이는 6DoF Couch의 Daily IGRT QA를 수행함에 있어서 유용할 것이라 사료된다.