• International Journal of Ocean System Engineering
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• 제1권4호
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• pp.222-229
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• 2011

In this paper, we present the concept and main mission of the Crabster, an underwater walking robot. The main focus is on the modeling of drag and lift forces on the legs of the robot, which comprise the main difference in dynamic characteristics between on-land and underwater robots. Drag and lift forces acting on the underwater link are described as a function of the relative velocity of the link with respect to the fluid using the strip theory. Using the translational velocity of the link as the rotational velocity of the joint, we describe the drag force as a function of joint variables. Generalized drag torque is successfully derived from the drag force as a function of generalized variables and its first derivative, even though the arm has a roll joint and twist angles between the joints. To verify the proposed model, we conducted drag torque simulations using a simple Selective Compliant Articulated Robot Arm.

• 전자공학회논문지B
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• 제29B권10호
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• pp.37-45
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• 1992

For a precise manipulator control in the presence of environmental uncertainties, it has long been recognized that the robot should be controlled in a task-referenced space. In this respect, an effective visual servo control system for robot manipulators based on neural networks is proposed. In the proposed control system, a Backpropagation neural network is used first to learn the mapping relationship between the robot's joint space and the video image space. However, in the real control loop, this network is not used in itself, but its first and second derivatives are used to generate servo commands for the robot. Second, and Adaline neural network is used to identify the approximately linear dynamics of the robot and also to generate the proper joint torque commands. Computer simulation has been performed demonstrating the proposed method's superior performance. Futrhermore, the proposed scheme can be effectively utilized in a robot skill acquisition system where the robot can be taught by watching a human behavioral task.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.847-848
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• 2013

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.266-271
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• 1992

This paper presents a new stable composite control law for the flexible joint robot manipulators, which incorporate the additional stabilizing control law with sliding property. The singularly perturbated models include inertia moments functions of the deformations of actuator. The newly defined fast controller variable is computed from the corrected reduced-order model without additional computational loads. The simulations for 2 DOF flexible joint manipulator show that the proposed schemes are more stable than conventional one, and especially effective for the manipulator with high joint-flexibilities.

• 센서학회지
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• 제27권2호
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• pp.105-111
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• 2018

In this paper, a torque sensor is designed and fabricated to measure the knee joint torque of a walking assist robot for stroke patients. The torque sensor sensing part was modeled on the link of the part connected to the knee joint motor. The torque capacity of the knee joint was calculated by simulation and the size of the torque sensor sensing part was designed using the finite element method. The torque sensor was fabricated by attaching a strain gauge to the sensing part. Characteristic experiments were conducted to characterize the torque sensor, and the torque sensor was calibrated to utilize it for the control of the walking assist robot. As a result of the characteristics test, the reproducibility error and the nonlinearity error of the torque sensor were 0.03% and 0.04%, respectively. Therefore, it is considered that the developed torque sensor can be used to measure the torque applied to the knee joint when walking on a walking assist robot.

• 한국산업융합학회 논문집
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• 제21권2호
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• pp.53-62
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• 2018

This study propose a new approach to control the optimal working path of vertical type articulated robot with translation joint for trimming working process automation in forging manufacturing process. The basic structure of the proposed robotic joints controller consists of a Proportional-Intergral controller and a Proportional-Derivative controller in parallel. The proposed control scheme takes advantage of the properties of the fuzzy PID controllers. The proposed method is suitable to control of the trajectory and path control in cartesian space for vertical type articulated robot manipulator. The results illustrates that the proposed fuzzy computed torque controller is more stable and robust than the conventional computed torque controller. The reliability is varified by simulation test for vertical type s articulated robot with seven joints including one trqanslation joint.

• 한국정보통신학회논문지
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• 제5권4호
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• pp.756-765
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• 2001

An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.

• 대한기계학회논문집A
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• 제21권8호
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• pp.1250-1258
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• 1997

This paper reports on the development of a new foot for a quadrupedal jointed-leg type walking robot. The foot has 2 toes, one at the front and the other at the rear side, for stable landing on uneven ground by point contact. The toes can move up and down independantly, guided by double-wishbone shaped parallel links which enable the lower leg to rotate with respect to a remote center on the ground surface. The motion of each toe is damped by a hydropneumatic shock absorber integrated in the foot in order to absorb the dynamic landing shock. Furthermore, the new foot can reduce the maximum hip joint drive torque by shortening the moment arm length between the hip joint and the landing force vector on the ground. Intensive experiments were carried out in this study by using a one-leg walking model to investigate the soft landing performance of the foot which could be hardly offered by conventional robot feet such as a flat plate with a gimbal type ankle joint. And it was confirmed that the hip joint torque of the leg walking on the flat surface could be reduced remarkably by using the new foot.

• 한국지능시스템학회논문지
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• 제22권5호
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• pp.617-623
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• 2012

본 논문에서는 4족 로봇의 허리 관절을 이용하여 효율적인 경사면 보행을 위한 걸음새 생성 방법을 제안한다. 허리 관절을 갖는 4족 로봇의 기구학적 모델은 Denavit-Hartenberg 표현 방법과 대수적 방법을 이용하여 유도하고, 다리 이동 순서는 물결 걸음새(wave gait)를 사용한다. 한편 제안한 걸음새 생성 방법에서는 기구적 제한과 보폭의 감소를 완화하기 위해 경사면의 경사도에 따라 적절한 상체 및 하체의 허리 관절각을 결정하고, 에너지 안정도 여유(energy stability margin)를 증가시키기 위해 도달 영역(workspace)의 탐색을 통해 발끝 위치를 결정한다. 마지막으로, 컴퓨터 모의 실험을 통해 본 논문에서 제안한 알고리듬의 효용성 및 실제 적용 가능성을 검증한다.

• 대한산업공학회지
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• 제25권3호
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• pp.382-392
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• 1999

Industrial robots have increased in both the number and applications in today's material handling systems. However, traditional approaches to robot controling have had limited success in complicated environment, especially for real time applications. One of the main reasons for this is that most traditional methods use a set of kinematic equations to figure out the physical environment of the robot. In this paper, a neural network model to solve robot manipulator's inverse kinematics problem is suggested. It is composed of two Self-Organizing Feature Maps by which the workspace of robot environment and the joint space of robot manipulator is inter-linked to enable the learning of the inverse kinematic relationship between workspace and joint space. The proposed model has been simulated with two robot manipulators, one, consisting of 2 links in 2-dimensional workspace and the other, consisting of 3 links in 2-dimensional workspace, and the performance has been tested by accuracy of the manipulator's positioning and the response time.