• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.217-218
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• 2012

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.273-282
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• 2013

The purpose of this study was to investigate effect of robot-assisted hand rehabilitation(Amadeo(R)) on hand motor function in chronic stroke patients. This study used a single-subject experimental design with multiple baselines across individuals. Three chronic stroke survivors with mild to sever motor impairment took part in study. Each participants had 2 weeks interval of starting intervention. Participants received robot-assisted therapy(45min/session. 3session/wk for 6wks). Finger active range of motion(AROM) was assessed by Range of Assessment program in Amadeo(R), and test-retest reliability was verified using Pearson correlation analysis. To investigate effect of Amadeo(R), finger AROM was measured immediately after each sessions and Fugl-Meyer Assessment of Upper extremity, Motor Activity Log, Nine hole peg board test and Jebsen-Taylor hand motor function test were assessed at pre-post intervention. Results were analyzed by visual analysis and comparison of pre-post tests. The test-retest reliability of Range of Assessment was good(r=.99). After robot-assisted therapy, finger AROM of participant 1, 2, and 3 was respectively improved by 18%, 3.6%, and 6% each. Hand motor function of participant 1, 3 was improved on all four tests, but not effect in participant 2. Robot-assisted hand rehabilitation could improve finger AROM and effect on hand motor function in chronic stroke patients.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.87-94
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• 2020

This paper introduces a method to control an industrial robot arm to imitate the movement of the human arm and hand using electromyography (EMG) signals. The proposed method is implemented on the UR3 robot that is a popular industrial robot and a MYO armband that measure the EMG signals generated by human muscles. The communications for the UR3 robot and the MYO armband are integrated in the robot operating system (ROS) that is a middle-ware to develop robot systems easily. The movement of the human arm and hand is detected by the MYO armband, which is utilized to recognize and to estimate the speed of the movement of the operator's arm and the motion of the operator's hand. The proposed system can be easily used when human's detailed movement is required in the environment where human can't work. An experiments have been conducted to verify the performance of the proposed method using the teleoperation of the UR3 robot.

• Journal of the Ergonomics Society of Korea
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• v.6 no.2
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• pp.19-28
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• 1987

If an error occurs in the automatic mode when the advanced teleoperator system performs a task in hostile environment, then the mode changes into the manual mode. The operation by program and the operation by hyman recover the error in the manual mode. The system resumew the automatic mode and continues the given task. In order to utilize the inverse kinematics as means of the operation by program in the manual mode, Lee and Nagamachi determined the end point of the robot trajectory planning which varied with the height of the task object recognized by a T.V monitor, solved the end point by the fuzzy set theory, and controlled the position of the robot hand by the inverse kinematics and the posture of the robot hand by the operation by human. But the operation by human did take a lot of task time because the position and the posture of the robot hand were separately controlled. To reduce the task time by human, this paper developes an error recovery expert system (ERES). The position of the robot hand is controlled by the inverse kinematics of the cartesian coordinate system to the end point which is deter- mined by the fuzzy set theory. The posture of the robot hand is controlled by the modulality of the robot hand's motion which is made by the posture of the task object. The knowledge base and the inference engine of the ERES is developed using the muLISP-86 language. The experimental results show that the average task time by human the ERES which was performed by the integration of the position and the posture control of the robot hand is shorter than that of the research, done by the preliminary experiment, which was performed by the separation of the position and the posture control of the robot hand. A further study is likely to research into an even more intelligent robot system control usint a superimposed display and digitizer which can present two-dimensional coordinate of the work space for the convenience of human interaction.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.404-414
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• 2000

This paper addresses the development of a 3-fingered humanoid robot hand system and a real-time grasp synthesis of multifingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by the multifingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign physical constraints of the humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics inspired from human's grasping behaviors. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables the grasp posture to be changable within two-finger and three-finger grasps. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our robot hand system by solving the 2- or 3-finger grasp synthesis.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.411-416
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• 2006

This paper describes the development of a 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot's hand. In order to safely grasp an unknown object, robot's hand should measure the weight of an object and the force of grasping direction simultaneous. But, in the published papers, the grippers and hands equippd with the force sensor that could only measure the force of grasping direction, and grasped objects using their sensors. These grippers and hands can't safely grasp unknown objects, because they can't measure the weight of it. Thus, it is necessary to develop 3-axis force sensor that can measure the weight of an object and the force of grasping direction for an intelligent gripper. In this paper, 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot's hand was developed. In order to fabricate a 3-axis finger force sensor, the sensing elements were modeled using parallel plate beams, and the theoretical analysis was performed to determine the size of sensing elements, then the 3-axis finger force sensor was fabricated. Also, the characteristic test of the developed 3-axis finger force sensor was performed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.751-752
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• 2008

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.53-59
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• 2022

In this paper, a mobile robot capable of remote control is designed in consideration of the user's various work environments. Specifically, a mobile remote work robot that moves in a predetermined direction and can perform a series of tasks in synchronization with the user's hand movements, and a control system and control method for controlling the robot were proposed. It was implemented using a robot hand and a wheel for movement to assist in tasks such as transporting dangerous goods or heavy goods. In order to evaluate the performance of the developed robot, the maximum weight that can be carried by the robot hand and the movable inclination of the robot were tested, and the test evaluation results satisfied most of the targeted design specifications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.443-444
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• 2011

• Journal of Sensor Science and Technology
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• v.16 no.3
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• pp.211-219
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• 2007

This paper describes the development of 6-axis force/moment sensor for a humanoid robot. In order to walk on uneven terrain safely, the robot's foot should perceive the applied forces Fx, Fy, Fz and moments Mx, My, Mz to itself, and be controlled by the foot using the forces and moments. Also, in order to grasp unknown object safely, the robot's hand should perceive the weight of the object using the mounted 6-axis force/moment sensor to its wrist, and be controlled by the hand using the forces and moments. Therefore, 6-axis force/moment sensor should be necessary for a humanoid robot's hand and foot. In this paper, 6-axis force/moment sensor for a humanoid robot was developed using many PPBs (parallel plate-beams). The structure of the sensor was newly modeled, and the sensing element of the sensor was designed using theoretical analysis. Then, 6-axis force/moment sensor was fabricated by attaching strain-gages on the sensing elements, and the characteristic test of the developed sensor was carried out. The rated outputs from theoretical analysis agree well with the results from the experiments.