• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.2
• /
• pp.127-134
• /
• 2004

In this paper, human motor behaving model based sensory motor coordination(SMC) algorithm is implemented on robotic grasping task. Compare to conventional SMC models which connect sensor to motor directly, the proposed method used biologically inspired human behaving system in conjunction with SMC algorithm for fast grasping force control of robot arm. To characterize various grasping objects, pressure sensors on hand gripper were used. Measured sensory data are simultaneously transferred to perceptual mechanism(PM) and long term memory(LTM), and then the sensory information is forwarded to the fastest channel among several information-processing flows in human motor system. In this model, two motor learning routes are proposed. One of the route uses PM and the other uses short term memory(STM) and LTM structure. Through motor learning procedure, successful information is transferred from STM to LTM. Also, LTM data are used for next moor plan as reference information. STM is designed to single layered perception neural network to generate fast motor plan and receive required data which comes from LTM. Experimental results showed that proposed method can control of the grasping force adaptable to various shapes and types of greasing objects, and also it showed quicker grasping-behavior lumining time compare to simple feedback system.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.12
• /
• pp.47-53
• /
• 2018

Various types of robotic arms are being used for industrial purposes, particularly with the small production of multi-products, and the importance of the gripper, which can be used in industrial fields, is increasing. This study evaluated a variable stiffness mechanism gripper that can change the stiffness using the nonlinearity of a flexible material. A prototype of the gripper was fabricated and examined to confirm the change in stiffness. The previous gripper was unable to grip objects in some situations with three variable stiffness mechanism. In addition, these mechanisms were not balanced and rarely rotated when the object was gripped. Therefore, a new type of gripper was needed to solve this problem. Inspired by the movements of the human palm and Venus Flytrap, a new type of a variable stiffness soft robot hand was designed. The possibility of grasping could be increased by interlocking the palm folding mechanism by pulling the tendon attached to the variable stiffness mechanism. The soft robotic hand was used to grasp objects of various shapes and weights more stably than the previous variable stiffness mechanism gripper. This new variable stiffness soft robot hand can be used selectively depending on the application and environment to be used.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.5
• /
• pp.941-946
• /
• 2021

This paper is a study on the design and implementation of a rehabilitation wearable robotic hand that reduces weight and volume by using a 3D printer and a motor. Rehabilitation wearable robots are important not only for the effect of rehabilitation but also for ease of use. However, most of the currently researched and developed rehabilitation exoskeleton robots are heavy in volume and weight, or they have to be used in place. Therefore, a wearable robot that is easy to wear and does not burden the user is required, so a lightweight electric rehabilitation wearable robot hand is proposed. A 3D printer was used to reduce the weight and volume and to make it easier to wear. In addition, to increase portability, the structure was simplified by adopting an electric method rather than a pneumatic method. Finally, the effectiveness was examined through the experiment of the lightweight electric rehabilitation wearable robot hand.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.11 s.176
• /
• pp.82-90
• /
• 2005

Recently, the in-line vision inspection has become the subject of growing research area in the visual control systems and robotic intelligent fields that are required exact three-dimensional pose. The objective of this article is to study the pc based in line visual inspection with the hand-eye structure. This paper suggests three dimensional structured light measuring principle and design method of laser sensor header. The hand-eye laser sensor have been studied for a long time. However, it is very difficult to perform kinematical analysis between laser sensor and robot because the complicated mathematical process are needed for the real environments. In this problem, this paper will propose auto-calibration concept. The detail process of this methodology will be described. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed in-line inspection module demonstrate the successful operation with hole, gap, width or V edge.

• Journal of the Ergonomics Society of Korea
• /
• v.15 no.2
• /
• pp.165-176
• /
• 1996

Hand posture and force, which define aspects of the way an object is grasped, are features of robotic manipulation. A means for specifying these grasping "flavors" has been developed that uses an instrumented glove equipped with joint and force sensors. The new grasp specification system is being used at the Pennsylvania State University (Penn State) in a Virtual Reality based Point-and-Direct (VR-PAD) robotics implementation. In the Computer Integrated Manufacturing (CIM) Laboratory at Penn State, hand posture and force data were collected for manipulating bricks and other items that require varying amounts of force at multiple pressure points. The feasibility of measuring desired grasp characteristics was demonstrated for a modified Cyberglove impregnated with FSR (Force Sensitive Resistor) pressure sensors in the fingertips. A joint/force model relating the parameters of finger articulation and pressure to various lifting tasks was validated for the instrumented "wired" glove. Operators using such a modified glove may ultimately be able to configure robot grasping tasks in environments involving hazardous waste remediation, flexible manufactruing, space operations and other flexible robotics applications. In each case, the VR-PAD approach improved the computational and delay problems of real-time multiple- degree-of-freedom force feedback telemanipulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.566-571
• /
• 1994

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

• Journal of the Korean Society for Precision Engineering
• /
• v.10 no.2
• /
• pp.14-21
• /
• 1993

Pneumatic actuators have greater power to weight ratio than electric ones, but they have been rarely used as robotic actuators because of poor accuracy resulted from nonliearity of air. On the other hand, electric servo motors have glld controllability, but they have poor power to weight ratio. For the heavy load handling robot a combined actuating method was developed for vertical and horizontal axes of RISTBOT-ll which handles up to 250kgf load. In this paper, the control method is implemented and analyzed for the manufactured heavy load handling robot.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.592-600
• /
• 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 Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.1
• /
• pp.41-47
• /
• 2000

A better tracking performance can be achieved, if visual sensors such as CCD cameras are used in controling a robot manipulator, than when only relative sensors such as encoders are used. However, for precise visual servoing of a robot manipulator, an expensive vision system which has fast sampling rate must be used. Moreover, even if a fast vision system is implemented for visual servoing, one cannot get a reliable performance without use of robust and stable inner joint servo-loop. In this paper, we propose a dynamic control scheme for robot manipulators with eye-in-hand camera configuration, where a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to be robust to parameter uncertainty, disturbances, low sampling rate, etc.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.05a
• /
• pp.680-683
• /
• 2022

본 논문은 가상 환경에서 사용자 및 로봇이 손을 이용하여 직관적으로 가상 물체와 상호작용하도록 하는 파지 방법을 제안한다. 제안한 방법은 사람 손과 로봇 손의 구조적인 차이를 고려하여 사람과 로봇에게 범용적으로 적용할 수 있도록 물리적 상호작용이 가능한 입자를 가상 손에 붙이고, 이를 이용하여 가상 물체를 파지하는 방법이다. 제안한 파지 방법을 사람과 로봇에 적용하여 실험한 결과, 임의의 다양한 물체를 직관적으로 파지할 수 있었고 높은 성공률을 보였다.