• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.76-76
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• 2000

The calibration of the robot system with a visual sensor consists of robot, hand-to-eye, and sensor calibration. This paper describe a new technique for computing 3D position and orientation of a 3D sensor system relative to the end effect of a robot manipulator in an eye-on-hand robot configuration. When the 3D coordinates of the feature points at each robot movement and the relative robot motion between two robot movements are known, a homogeneous equation of the form AX : XB is derived. To solve for X uniquely, it is necessary to make two robot arm movements and form a system of two equation of the form: A$_1$X : XB$_1$ and A$_2$X = XB$_2$. A closed-form solution to this system of equations is developed and the constraints for solution existence are described in detail. Test results through a series of simulation show that this technique is simple, efficient, and accurate fur hand/eye calibration.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.774-781
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• 2003

The important factors that cause position error in X-Y robot are inertial force, frictions and spring distortion in screw or coupling. We have to estimate these factors precisely to correct position errors, Which is very difficult. In this paper, we makes systems to inspect metal stencil which is used to print solder paste on pads of SMD of PCB with low precision X-Y robot and vision system. To correct position error that is caused by low precision X-Y robot, we defines position error vector that is formed with position of objects that exist in reference and camera image. We apply MHT(Modified Hough Transformation) for the aim of determining the dominant position error vector. We modify reference image using extracted dominant position error vector and obtain reference image that is the same with camera image. Effectiveness and performance of this method are verified by simulation and experiment.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.77-84
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• 2006

This paper describes the design and implementation of a robot's gripper control system. In order to safely grasp an unknown object using the robot's gripper, the gripper should detect the force of gripping direction and the force of gravity direction, and should perform the force control using the detected forces and the robot's gripper control system. In this paper, the robot's gripper control system is designed and manufactured using DSP(Digital Signal Processor), and the gripper is composed of two 6-axis force/moment sensors which measures the Fx force(force of x-direction), Fy force, Fz force, and the Mx moment(moment of x-direction), My moment, Mz moment at the same time. The response characteristic test of the system is performed to determine the proportional gain Kp and the integral gain Ki of PI controller. As a result, it is shown that the developed robot's gripper control system grasps an unknown object safely.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.144-149
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• 2001

There are many types of seam tracking methods actually used in industrial spot. Lately, Non-contact sensor technics are mostly used because non-contact sensor has more advantage than contact sensor in many parts. This paper also concerned about fiber sensor a kind of non-contact sensor. X-Y robot and fiber sensor scan the seam tracking to be weld. After scanning, X-Y robot moves the first working point of being scanned and welding starts automatically. It makes an experiment on some types of Seam tracking like straight line tracking, leaned line tracking and curved line tracking to confirm how well the fibers sensor tracks the seam pass to be weld. And the seam pass that had been tracked was welded by inverter $CO_2$ voiding machine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.558-561
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• 2000

There are many types of seam tracking methods actually used in industrial spot. Lately, Non-contact sensor technics are mostly used because non-contact sensor has more advantage than contact sensor in many parts. This paper also concerned about fiber sensor a kind of non-contact sensor. X-Y robot and fiber sensor scan the seam tracking to be weld. After scanning, X-Y robot moves the first working point of being scanned and welding starts automatically. It makes an experiment on some types of Seam tracking like straight line tracking, leaned line tracking and curved line tracking to confirm how well the fibers sensor tracks the seam pass to be weld. And the seam pass that had been tracked was welded by inverter CO2 welding machine.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.185-191
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• 2008

In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.

• Journal of Biosystems Engineering
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• v.30 no.5 s.112
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• pp.293-298
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• 2005

The purpose of this study was the development of a multi-joint robot manipulator for milking robot system. The multi-joint robot manipulator was controlled by 5 drivers with driver controller through the position information obtained from the image processing system. The robot manipulator to automatically attach each teat cup to the teats of a milking cow was developed and it's motion was accurately measured with error rate. Results were as follows. 1. Maximum errors in position accuracy were 4mm along X-axis, 4.5mm along Y-axis and 0.9mm along Z-axis. Absolute distance errors were maximum 4.8mm, minimum 2.7mm, and average 3.6mm. 2. Errors of repeatability were maximum 3.0mm along X-axis, 3.0mm along Y-axis, and 0.5mm along Z-axis. Distance error values were maximum 3.2mm, minimum 2.2mm, and average 2.5mm. It is envisaged that multi-joint robot manipulator can be applicate to milking robot system being developed in consideration of the experiment results.

• Journal of Animal Environmental Science
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• v.6 no.2
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• pp.105-112
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• 2000

The objective of this study was to determine the teat locations and to develop a teat cup handling system operated by a robot. The results of this study were summarized as follows: 1. The teat cup attaching and detaching operation system developed in this study consists of a control computer, a five-dimensional robot(PERFORMER-MK2), a DC servo gripper, a robot controller, two CCD-cameras (WV-vp410), an image grabber board(DT3153), a model cow, and a teat cup unit. 2. The coordinates of teat locations were measured by a stereo image processing unit. The error ranges of teats coordinates measured were (x, y, z) = (0.83, 1.95, 0.81) mm. When those were transferred into the Robot Coordinate System(RCS) coordinate, the total error ranges measured were x = 0.9 mm, y = 2.0 mm, z = 0.9 mm. 3. The rates of success of teat cup attaching and detaching operation by a robot system were 91.5% on average; the operation time needed were 27.8 sec. Total working hours for the teat cup handling including image processing were 86.1 sec.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2365-2368
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• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field($B_{x}$, $B_{y}$, $B_{z}$) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field($B_{x}$, $B_{y}$, $B_{z}$). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot (including mobile robot dynamics and steering) was used to verify the steering performance of the mobile robot controller using the fuzzy logic. Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation. Also, we know that proposed control algorithm was applied to real autonomous mobile robot.