• 한국CDE학회논문집
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• 제16권6호
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• pp.437-448
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• 2011

A robotic spatial augmented reality (RSAR) system combines a robotics technology with a spatial augmented reality system (SAR) where cameras are used to recognize real objects and projectors augment information and user interface directly on the surface of the recognized objects, rather than relying on handheld display devices. Moreover, a robotic module is actively used to discover and utilize the context of users and environments. The control of a RSAR system involves several issues from different technical fields such as classical inverse kinematics of motors where projector-camera pairs are mounted, inverse projection problems to find appropriate internal/external parameters of projectors and cameras, and image warping in graphics pipeline to compensate the kinematic constraints. In this paper, we investigate various control issues related to a RSAR system and propose basic approaches to handle them, specially focused on the prototype RSAR system developed in ETRI.

• 한국생산제조학회지
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• 제22권2호
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• pp.256-262
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• 2013

This paper presents a linear path control algorithm for NeuroMate robot in a skull drilling system. For the path control inverse kinematics of the robot is analyzed and a linear interpolation algorithm is presented. A geometric approach is used for solving inverse kinematic equations for the robot. Four feasible solutions are found through the approach. The approach gives geometric insights for selecting the best solution from the feasible solutions. The presented linear interpolation algorithm computes a next position considering current velocity and remaining distance to the target position. Presented algorithm is implemented and tested in a skull drilling system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.65-68
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• 1995

This paper describes trajectory generation of a riobot arm by self-organizing neural networks. These neural networks are based on competitive learning without a teacher and this algorithm which is suitable for problems in which solutions as teaching signal cannot be defined-e.g. inverse dynamics analysis-is adopted to the trajectory generation problem of a robot arm. Utility of unsupervised learning algorithm is confirmed by applying the approximated solution of each joint calculated through learning to an actual robot arm in giving the experiment of tracking for reference trajectory.

• 로봇학회논문지
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• 제15권3호
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• pp.212-220
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• 2020

This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제8권4호
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• pp.367-375
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• 2002

역운동학 알고리즘은 다관절체의 엔드 이펙터를 제어하기 위한 매우 유용한 방법이다. 대부분의 역운동학 처리 과정에서 주된 관심사는 다관절체가 가지는 자세의 형태 자체가 아니라 제어되는 다관절체의 엔드 이펙터의 위치와 방향이다. 그러나 삼차원 캐릭터 애니메이션과 같은 종류의 응용 분야에 있어서는 엔드 이펙터의 정확한 위치와 방향보다는 다관절체의 전체적으로 자연스러운 자세 자체가 훨씬 더 중요한 요소이다. 실제로 애니메이터가 기존의 역운동학 기법을 사용해서 인체와 같이 다수의 물리적인 제약조건을 가지는 인간형 삼차원 캐릭터의 자세를 자연스럽게 제어하기 위해서는 많은 시행착오를 겪어야만 하기 때문에 이를 보완하는 특별한 알고리즘이 요구된다. CCD(Cyclic Coordinate Descent) 알고리즘은 기하학적인 검색을 통해 원하는 위치에 엔드 이펙터를 위치시키는 해를 구하는 역운동학 방식의 하나로서 사용자 상호작용을 통한 다관절체의 자세 제어에 적합하다. 그러나 CCD 알고리즘의 해는 초기 자세에 강력하게 종속되어 있기 때문에 초기 자세에 따라서 서로 다른 많은 해들을 얻게 된다. 본 논문에서는 인간형 캐릭터의 자세 제어를 위해 균등 자세 지도를 이용한 귀납적 역운동학 알고리즘을 제안한다. 균등자세 지도의 학습 알고리즘은 인간의 다양한 자세를 왜곡 없이 양자화하기 때문에 균등 자세 지도를 이용해서 기술되는 모든 자세들은 사실적인 자세임을 보장한다. 그러므로 균등 자세 지도를 통해 계산된 다관절체의 엔드 이펙터가 원하는 삼차원 위치와 가장 가까운 자세를 추출해 냄으로써 자연스러운 자세를 가지는 역운동학의 결과를 얻을 수 있다. 이러한 방식은 키 프레임 기반 삼차원 캐릭터 애니메이션의 제작과 3차원 게임, 그리고 가상 현실 등의 분야에 유용하게 적용될 수 있다.

• 한국산업융합학회 논문집
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• 제23권2_2호
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• pp.313-321
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• 2020

In this paper, two types of linear actuation methods for the previously proposed adaptive gripper are presented, which includes actual parallelogram inside a five-bar mechanism and has the advantages of smaller actuation torque and larger stroke over the commercial adaptive gripper by RobotiQ. The forward/inverse kinematics and statics analyses for two types of linear actuations are derived. From the inverse kinematics and statics analyses, linear actuation type I is selected and the gripper prototype is designed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.137-138
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• 2010

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.803-804
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• 2011

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.255-258
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• 2001

This introduces a improved method of the forward kinematics analysis, which finds the 6DOF motions and velocities from the given six cylinder lengths in the Steward platform. The numerical method(Newton Raphson Mehotd)of the forward kinematics analysises has the disadvantage of the long calculated time. To overcome this, we propose the competitive method that determine a proper initial value. Through the competitive method, we can select a proper initial value so that the calculate time is reduced. therefore we can give the property of the real time process to the forward kinematics analysis. We show the result comparing between general Newton-Raphson method and proposed one. From the result we verify the performance of the proposed method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.224-228
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• 2000

In this paper, the kinematics of the new type of parallel manipulator is studied, and neural network is applied to solve the forward kinematics problem. The parallel manipulator, called a Stewart platform, has an easy and unique solution about the inverse kinematics, however the forward kinematics is difficult to get the solution because of the lack of an efficient algorithm due to its highly nonlinearity. This paper proposes the neural network scheme as an alternative Newton-Raphson method. The neural network is found to improve its accuracy by adjusting the offset of the result obtained.