• 전기학회논문지
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• 제67권3호
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• pp.427-432
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• 2018

This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.696-702
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• 2004

An optimal trajectory generation algorithm for capturing a moving object by a mobile robot in real-time is proposed in this paper. The linear and rotational velocities of the moving object are estimated using the Kalman filter, as a state estimator. For the estimation, the moving object is tracked by a 2-DOF active camera mounted on the mobile robot, which enables a mobile manipulator to track the mobile robot until the capturing moment. The optimal trajectory for capturing the moving object is dependent on the initial conditions of the mobile robot as well as the moving object. Therefore, real-time trajectory planning for the mobile robot is definitely required for the successful capturing of the moving object. The performance of proposed algorithm is verified through the real experiments and the superiority is demonstrated by comparing to other algorithms.

• 대한의용생체공학회:의공학회지
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• 제15권4호
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• 로봇학회논문지
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• 제12권3호
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• pp.322-331
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• 2017

In this paper we present a novel robotic palpation method for the lump shape estimation using contact pressure distribution. Many previous researches about the robotic palpation have used a stiffness map, which is not suitable to obtain geometrical information of a lump. As a result, they require a large data set and long palpation time to estimate the lump shape. Instead of using the stiffness map, the proposed palpation method uses the difference between the normal force direction and the surface normal to detect the lump boundary and estimate its normal. The palpation trajectory is generated by the normal of the lump boundary to track the lump boundary in real-time. The proposed approach requires small data set and short palpation time for the lump shape estimation since the shape can be directly estimated from the optimally generated palpation trajectory. An experiment result shows that our method can find the lump shape accurately in real-time with small data and short time.

• 한국기계가공학회지
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• 제10권3호
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• pp.33-38
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• 2011

A cubic spline trajectory planner with arc-length parameter is formulated with estimation by summing up to the 3rd order in Taylor's expansion. The PVAJT motion planning is presented to reduce trajectory calculation time at every cycle time of servo control loop so that it is able to generate cubic spline trajectory in real time. This method can be used to more complex spline trajectory. Several case studies are executed with different values of cycle time and sampling time, and showed the advantages of the PVAJT motion planner. A DSP-based motion controller is designed to implement the PVAJT motion planning.

• 한국산업정보학회논문지
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• 제20권5호
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• pp.1-11
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• 2015

본 논문은 궤적데이터마이닝의 2차 회귀분석 기법을 이용하여 나로우주센터 내 원격자료수신장비에서 우주발사체의 실시간 비행궤적을 보다 정확하게 추정하기 위한 방법을 제시하고 있다. 원격자료수신장비는 추적손실 없이 실시간으로 우주발사체의 비행위치와 상태정보를 수신하기 위한 정확한 위치추정 알고리즘이 필요하다. 따라서 나로호 1차 발사 시, 기존 보간법에 의한 원격자료수신장비 안테나의 거친 구동특성을 보완하고 안정적인 발사체의 위치추정을 위한 2차 회귀기법을 고려하였다. 성능분석을 위해 나로호 1차 비행시험데이터를 사용하였고, 수학적 모델링을 통해 실시간 발사체의 비행위치정보를 추정한 결과가 분석되었다. 분석결과, 궤적데이터마이닝의 2차 회귀기법을 적용한 위치추정알고리즘이 기존의 보간법에 의한 위치추정알고리즘보다 향상된 안테나 구동특성 및 추정정확도를 보였다.

• Journal of Astronomy and Space Sciences
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• 제22권4호
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• pp.501-512
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• 2005

본 논문에서는 우주개발 중장기계획에 따라 개발 중인 KSLV-I 우주발사체가 나로 우주센터에서 발사될 경우를 가정하여 확장칼만필터와 Unscented 칼만필터를 통한 실시간 궤적추정 결과를 비교 분석하였다. 이를 위해 가상의 KSLV-I과 관측 레이더 3기를 바탕으로 실제 궤적을 생성하였으며, 관측자료는 실제 궤적에 관측오차를 고려하여 생성하였다. 이에 대해 초기 추정오차가 작은 경우와 큰 경우로 구분하고, 관측주기가 20Hz와 10Hz인 경우로 나누어 각각 두 필터를 적용해서 성능을 비교하였다. Unscented 칼만필터는 확장칼만필터보다 큰 초기 추정오차에 대해 수렴이 빠르고 정확도가 높으며, 느린 관측주기에도 우수한 성능을 보이는 것을 확인하였다.

• 제어로봇시스템학회논문지
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• 제19권7호
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• 한국통신학회논문지
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• 제39C권1호
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• pp.47-59
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• 2014

본 논문은 실내 환경에서의 엔터테인먼트 활용을 목적으로 쿼드로터형 비행체를 위한 비전 기반의 궤적 추종제어 시스템을 다룬다. 항공촬영 및 감시 등의 특수임무를 완수하기 위해 자율성이 강조되는 실외 비행체와 비교할 때, 엔터테인먼트를 목적으로 하는 실내 환경에서의 비행체를 위해서는 안정성 및 정밀성이 특히 고려된 호버링 및 궤적추종 기능 등이 요구된다. 이에, 본 논문은 동작생성, 자세추정, 궤적추종 모듈로 구성된 궤적추종 제어시스템을 제안한다. 동작생성 모듈은 매 시간에서의 3차원 자세로 기술되는 동작들에 대한 연속적인 시퀀스를 생성한다. 자세추정 모듈은 비행체에 장착된 원형 링 패턴의 인식을 통해 쿼드로터의 3차원 자세정보를 추정한다. 궤적추종 모듈은 동작생성 모듈과 자세추정 모듈로부터 제공되는 정보를 이용하여 쿼드로터 비행체의 3차원 위치를 실시간적으로 제어한다. 제안된 시스템의 성능은 단일 점 추종, 다점 추종, 곡선궤적 추종에 대한 실험을 통해 평가된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.