• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.161-167
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• 2006

In this paper, lateral force control of a mobile robot with slip is presented. First, the bicycle model of a mobile robot is derived for the front steering. Second, impedance force control algorithm is applied to regulate contact force with environment. The desired distance is specified conservatively inside the environment to guarantee to make contact. Different stiffness of environment has been tested for force tracking task. Simulation results show that the proposed control algorithm works well to maintain desired contact force on the environment.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.657-660
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• 2003

Control of multi-link robot arms is a very difficult problem because of the highly nonlinear dynamics. Decentralized control scheme is developed for control of robot manipulators based on RBF(Radial Basis Function) Neural Networks. RBF Neural Networks is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional force. The compensation controller is also proposed to estimate the bound of approximation error so that the chattering effect of the control effort can be reduced. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for two-link robot manipulator are included to show the effectiveness of controller.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.758-763
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• 2003

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously, for making a robot's gripper. In order to safely grasp and unknown object using the robot's gripper, it should measure the force in the gripping direction and the force in the gravity direction, and perform the force control using the measured forces. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of made sensor was performed. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object was performed using it.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.801-806
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• 2014

LAS (Laparoscopy Assisted Surgery) has been substituted alternatively for traditional open surgery. However, when using a commercialized robot assisted laparoscopic such as Da Vinci, surgeons have encountered some problems due to having to depend only on information by visual feedback. To solve this problem, a haptic function is required. In order to realize the haptic teleoperation system, a force feedback and bilateral control system are needed. Previous research showed that the perturbation value estimated by a SPO (Sliding Perturbation Observer) followed a reaction force that loaded on the surgical robot instrument. Thus, in this paper, the force feedback problem of surgical robots is solved through the reaction force estimation method. This paper then introduces the possibility of the haptic function realization of a laparoscopic surgery robot using a bilateral control system. For bilateral control, the master uses an impedance control and the slave uses a SMC (Sliding Mode Control). The experiment results show that a torque and force sensorless teleoperation system can be implemented using a bilateral control structure.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.5-129
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• 2001

When a robot manipulator performs some task like grinding or assembling, not only the position control but also the force control of the tools connected to the robot must be controlled. But at this time We were received the uncertainty problems of system information for the force control, for example disturbance, senor resolution and measurement noise. Therefore we proposed fuzzy logic control method instead of existing control theory for the robot manipulator control, for example PID control method. In this paper, We proposed hybrid position/force control of robot manipulator using fuzzy logic control method. To show the validity of the proposed fuzzy controller, We compared fuzzy controller with conventional PID controller.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.89-96
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• 2009

This paper describes the intelligent robot's hand with three finger sensors for a humanoid robot. In order to grasp an unknown object safely, the intelligent robot's hand should measure the mass of the object, and determine the grasping force using the mass, finally control the grasping force using the finger sensors and the controller. In this paper, the intelligent robot's hand for a humanoid robot was developed. First, the six-axis force/moment sensor was manufactured. second, three finger force sensors were designed and fabricated, third, the high-speed controller was manufactured using DSP(digital signal processor), finally, the characteristic test for determining a grasping force and for grasping an unknown object safely It is confirmed that the hand could grasp an unknown object safely.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.130-134
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• 1992

The ability of a robot system to comply to an environment via the control of tool-environment interaction force is of vital for the successful task accomplishment in many robot application. This paper presents the implementation of external force control for two dimensional contour following task using a commercial robot system. Force accommodation is used since a constraint imposed in our work is not to modify the commercial robot system. A linear, decoupled model of two dimensional contour following system in the discrete time domain is derived first. Then the experimental verification of linear control is obtained using a PUMA 560 manipulator with standard Unimation controller, Astek FS6-120A six axis wrist force sensor attached externally to the arm and LSI-11173 microcomputer. Experimentally obtained data shows that the RMS contact force error is 0.8246 N when following the straight edge and 2.3768 N when following 40 mm radius curved contour.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.2
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• pp.232-240
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• 1998

This paper deals with a hybrid position/force control of a robot which is moving on the constrained object with constant force. The proposed controller is composed of a position and force controller. The position controller has a nonlinear compensator which is based on the dynamic robot model and the force controller is attached by feedforward element. A direct drive robot with hard nonlinearity which is controlled by the proposed algorithm has moved on the constrained object with a high stiffness and low stiffness. The results show that the proposed controller has more vibration suppression effects which is occurred to the constrained object with a high stiffness, than a existing feedback controller, and accurate force control can be obtained by comparatively a small feedback gain.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.54-61
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• 2004

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces $F_x$(x-direction force), $F_y$and $F_z$, and moments $M_x$ (x-direction moment), $M_y$ and $M_z$ simultaneously, for stable grasping of an unknown object. In order to safely grasp an unknown object using the robot's gripper, the force in the gripping direction and the force in the gravity direction should be measured, and the force control should be performed using the measured forces. Also, the moments $M_x$, $M_y$ and $M_z$ to accurately perceive the position of the object in the grippers should be detected. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of the fabricated sensor was performed, and the result shows that interference errors of the developed sensor are less than 3%. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object using the sensors was performed using it. The fabricated gripper could grasp an unknown object stably. Thus, the developed 6-axis robot's finger force/moment sensor can be used for robot's gripper.