• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.1-13
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• 2005

Kinematics of grasping and manipulation by a multi-fingered robotic hand where multi-fingertip surfaces are in contact with an object is solved. The surface of the object was represented by B-spline surfaces in order to model the objects of various shapes. The fingers were modeled by cylindrical links and a half ellipsoid fingertip. Geometric equations of contact locations have been solved for all possible contact combinations between the fingertip surface and the object. The simulation system calculated joint displacements and contact locations for a given trajectory of the object. Since there are no closed form solutions for contact or intersection between these surfaces, kinematics of grasping was solved by recursive numerical calculation. The initial estimate of the contact point was obtained by approximating the B-spline surface to a polyhedron. As for the simulation of manipulation, exact contact locations were updated by solving the contact equations according to the given contact states such as pure rolling, twist-rolling or slide-twist-rolling. Several simulation examples of grasping and manipulation are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.24-27
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• 2003

This paper discusses practical strategies for transition from a pinching to a power grasping, where a multi-fingered hand mounted on a robotic arm envelops a cylindrical object on a table. When the manipulation system grasps a cylindrical object like a pen on a desk, a complete enveloping is not impossible in the initial configuration. The system firstly pinches the object only with two or three fingers and then grasp it with fingers and a palm after regrasping. In this pinching-grasping transition maneuver, human unconsciously selects proper strategy according to some conditions including object dimensions and initial pinching positions. In this paper we therefore develop six possible strategies for this pinching-grasping transition and then investigate their performances for some objects with various dimensions and various grasping positions, using numerical simulations. Based on their results, effective strategies are implemented by using a hand-arm system.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.104-113
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• 2019

Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.58-64
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• 2024

The ability of the robot gripper to handle a wide range of objects significantly impacts its operational effectiveness. Among the robot grippers commonly used, the economically feasible choice is the relatively simple structure of a parallel gripper. To perform more densely packed tasks with a parallel gripper, it should be capable of handling small objects. Therefore, this study designs a parallel gripper mechanism equipped with assisting grippers to ensure smooth grasping of small objects. The parallel gripper is designed using a rack and pinion gear system, with two additional grippers on both side, and these assisting grippers are designed to be detachable. The two assisting grippers have different type of tip to grasp thin fabric shapes and thin stick shapes. The gripper prototype is used to verify the grasping capabilities for shapes achievable with a conventional parallel gripper and those intended for grasping with the assisting grippers through grasping experiments. Consequently, by equipping a conventional parallel gripper with assisting grippers as in this study, it becomes capable of handling a broader range of objects, in addition to its existing functionality.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.53-59
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• 2007

Several researches in 3D interaction have identified and extensively studied the four basic interaction tasks for 3D/VE applications, namely, navigation, selection, manipulation and system control. These interaction schemes in the real world or VE are generally suitable for interacting with small graspable objects. In some applications, it is important to duplicate real world behavior. For example, a training system for a manual assembly task and usability verification system benefits from a realistic system for object grasping and manipulation. However, it is not appropriate to instantly apply these interaction technologies to such applications, because the quality of simulated grasping and manipulation has been limited. Therefore, we introduce the intuitive and natural 3D interaction haptic interface supporting high-precision hand operations and realistic haptic feedback.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.216-223
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• 2015

Recently Manipulation capability is important for a robot. Interaction between a robot hand and objects can be properly controlled only is suitable sensors are available. Recently the tendency is to create robot hands more compact and high integrated sensors system, in order to increase the grasping capability and in order to reduce cabling through the finger, the palm and the arm. As a matter of fact, miniaturization and cabling harness represents a significant limitation to the design of small sized embedded sensor. Ongoing work is focusing on a flexible manipulation system, which consists of a dual flexible multi-fingered hand-arm system, and a dual active vision system.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.81-88
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• 2005

This paper attempts to derive the dynamic model of handling tasks in finger robot which grasps stable and manipulates a rigid object with some dexterity. Firstly, a set of differential equation describing dynamics of the manipulators and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. Secondly, the roblems of controlling both the forces of pressing object and the rotation angle of the object under the geometric constraints are discussed. The effect of geometric constraints of area-contacts between the link's end-effector and the object is analyzed and the model based on the differential-algebraic equations is presented. In this paper, the control method for dynamic stable grasping and enhancing dexterity in manipulating things is proposed. It is illustrated by computer simulation and the experiment that the control system gives the performance improvement in the dynamic stable grasping and nimble manipulating of the dual fingers robot with soft tips.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.4
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• pp.183-189
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• 2018

The focus of this paper is to design and control a three fingered hand system with eight axes for smart factory with an flexible controller, and to keep a useful big database for dynamic manipulation based on the experimental results. The weight of the hand module is only 1.2 kg, but flexible motion and powerful grasping are possible. To achieve such a flexible motion control of a robotic hand, we have developed a robust and precise fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. In this study, it was used three fingers with eight axes which is the optimal number to achieve a robust grasping diverse shape parts for smart factory.