In order to conduct a study on the importance of the wrist joint, which causes a lot of pain among middle-aged people, in relation to work related to musculoskeletal disorders, the effect of stretching on grasping power was studied. In order to compare the grasping power of the wrist for middle-aged people in their 50s, the experiment was conducted by comparing before and after the wrist joint motion stretching. According to the experimental results of wrist gripping power for the control group and the experiment group on wrist gripping power, it was investigated that stretching did not change much in increasing wrist gripping power, but stretching application had an effect on wrist gripping power. In terms of preventing musculoskeletal accidents, reducing pain due to degenerative diseases, and preventing accidents, stretching seems to have an effect when approaching, so it is considered that continuous stretching before and after work is necessary. Therefore, it is suggested that stretching time secured quantitatively through safety and health education before work is necessary.

Background: It is known that hand strength and fingertip force are used as an indicator of muscle strength and are also highly related to the various chronic symptoms and even lifespan. To use the individual fingertip force (IFF) as a quantitative index for clinical evaluation, the IFF should be measured and analyzed with various variables from various subjects, such as the normal range of fingertip force and the difference in its distribution by disease. Objects: We tried to measure and analyze the mean maximum IFF distribution during grasping a cylindrical object in healthy adults and patients with spinal cord injury (SCI). Methods: Five Force-sensitive resistor (FSR) sensors were attached to the fingertips of 24 healthy people and 13 patients with SCI. They were asked to grip the object three times for five seconds with their maximum effort. Results: The mean maximum IFF of the healthy adult group’s thumb, index, and middle finger was similar statistically and showed relatively larger than IFF of the ring and small finger. It is a 3-point pinch grip pattern. All fingertip forces of patients with SCI decreased by more than 50% to the healthy group, and their IFF of the middle finger was relatively the largest among the five fingertip forces. The cervical level injured SCI patients showed significantly decreased IFFs compared to thoracic level injured SCI patients. Conclusion: We expect that this study results would be helpful for rehabilitation diagnosis and therapy goal decision with robust further study.

It is necessary to make preventive method for the trauma and disturbance complications of orofacial area because athletic trauma are physical and mental defects. Since 1913, an italian boxer discussed mouth guard with dentist and used it. It was reported that mouth guard from field prevented trauma, increased the muscle force and activated electromyogram although the history of mouth guard wearing was short. The mouth guard has prevented the trauma and also increased the muscle force. The purpose was to study muscle force and activity of EMG with mouth guard wearing. It concluded that mouth could prevent trauma and increase the muscle force

이 글의 焦點은 학습자의 ‘漢字 語彙’ 意味 把握의 經路에 있다. 현행 교육과정에 따르면, ‘漢字語’, ‘한자 어휘’는 국어과의 어휘 교육, 한문과의 전 영역과 관련되는 학습 내용이다. 이 과제를 해결하기 위해, 『漢文』, 『국어』교과서에 기술된 한자 어휘 의미 提示 방식을 비평적으로 분석한다. 주지하듯이, 교과서의 주요 機能 가운데 하나는 교수의 節次와 학습의 過程 제시라고 할 수 있다. 곧, 교사에게는 교수 절차를 案內하는 자료의 하나로, 학습자에게는 학습 과정을 紹介하는 자료의 하나로 교과서는 활용된다. 그런데, 한자 어휘의 경우, 교과서에 제시된 어휘의 의미[뜻] 제시 방식이 바로 학습자의 한자 어휘 의미 파악의 一次 경로라고 볼 수 있다. 다시 말해, 교과서에 나타난 한자 어휘 의미 제시 방식을 통해 학습자는 한자 어휘의 의미를 파악할 수 있는 端緖와 학습 전략을 獲得하게 된다.우선, 한자 어휘 의미 파악의 ‘국어식’ 通路로 『국어 사전』에 登載된 어휘 풀이 에 근거한 이해 방식을 들 수 있다. 국어 體系를 따른 풀이는 한자어를 구성하는 한자의 形態素로써의 機能을 고려하지 않고, 현재의 시점에서 通用되는 의미를 중심으로 설명하는 것인데, 한자 어휘를 구성하는 개별 形態素인 한자의 字義와 단어의 짜임을 고려하지 않는다. 이 경로와 무관하지 않은 방식으로 ‘文脈的 정보의 활용’을 거론할 수 있다. 한자 어휘의 의미를 한자 어휘가 사용된 狀況 脈絡을 통하여 拾得하는 방식인데, 한자의 字義나 단어의 짜임과 無關한 점은 동일하다. 두 가지 경로 모두 한자 어휘 의미의 曲解와 誤用이 심화된다.이 글에서 한자어를 구성하는 형태소인 한자의 字義에 근거한 한자 어휘 의미 파악 경로를 강조했다. 한자 어휘를 구성하는 한자를 倂記하고, 한자 어휘의 의미에 적합한 한자의 음과 뜻을 羅列하여 학습자가 한자 어휘의 의미를 파악하는 방식인데, 한자 어휘 의미의 정확한 이해와 그 활용을 가능하게 한다. 한자어를 구성하는 統辭的 構造에 근거한 한자 어휘 이해 방식도 주목된다. 한자 어휘의 文法 構造를 고려한 한자 어휘 의미 제시는 학습자가 한자 어휘의 本義를 파악하는데 相補的이라고 할 수 있다. 결국, 학습자가 한자 어휘를 학습하는데, 국어 사전, 文脈, 언어적 환경 등의 요인도 작용하지만, 한자 어휘를 구성하는 한자의 字義, 자의에 근거한 語義, 그리고 어휘의 문법 구조가 한자 어휘 의미 파악의 주요 경로이다.

In this paper, we present a learning platform for robotic grasping in real world, in which actor-critic deep reinforcement learning is employed to directly learn the grasping skill from raw image pixels and rarely observed rewards. This is a challenging task because existing algorithms based on deep reinforcement learning require an extensive number of training data or massive computational cost so that they cannot be affordable in real world settings. To address this problems, the proposed learning platform basically consists of two training phases; a learning phase in simulator and subsequent learning in real world. Here, main processing blocks in the platform are extraction of latent vector based on state representation learning and disentanglement of a raw image, generation of adapted synthetic image using generative adversarial networks, and object detection and arm segmentation for the disentanglement. We demonstrate the effectiveness of this approach in a real environment.

This paper presents a control and operation system for a remotely operated vehicle (ROV). The ROV used in the study was equipped with a manipulator and is being developed for underwater exploration and autonomous underwater working. Precision position and attitude control ability is essential for underwater operation using a manipulator. For propulsion, the ROV is equipped with eight thrusters, the number of those are more than six degrees-of-freedom. Four of them are in charge of surge, sway, and yaw motion, and the other four are responsible for heave, roll, and pitch motion. Therefore, it is more efficient to integrate the management of the thrusters rather than control them individually. In this paper, a thrust allocation method for thruster management is presented, and the design of a feedback controller using sensor data is described. The software for the ROV operation consists of a robot operating system that can efficiently process data between multiple hardware platforms. Through experimental analysis, the validity of the control system performance was verified.

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.

The optimal grasping point of the object varies depending on the shape of the object, such as the weight, the material, the grasping contact with the robot hand, and the grasping force. In order to derive the optimal grasping points for each object by a three fingered robot hand, optimal point and posture have been derived based on the geometry of the object and the hand using the artificial neural network. The optimal grasping cost function has been derived by constructing the cost function based on the probability density function of the normal distribution. Considering the characteristics of the object and the robot hand, the optimum height and width have been set to grasp the object by the robot hand. The resultant force between the contact area of the robot finger and the object has been estimated from the grasping force of the robot finger and the gravitational force of the object. In addition to these, the geometrical and gravitational center points of the object have been considered in obtaining the optimum grasping position of the robot finger and the object using the artificial neural network. To show the effectiveness of the proposed algorithm, the friction cone for the stable grasping operation has been modeled through the grasping experiments.

This paper proposes a method to simultaneously estimate two degrees of freedom in wrist forces (extension - flexion, adduction - abduction) and one degree of freedom in grasping forces using Electromyography (EMG) signals of the forearms. To correlate the EMG signals with the forces, we applied a multi - layer perceptron(MLP), which is a machine learning method, and used the characteristics of the muscles constituting the forearm to generate learning data. Through the experiments, the similarity between the MLP target value and the estimated value was investigated by applying the coefficient of determination (R2) and root mean square error (RMSE) to evaluate the performance of the proposed method. As a result, the R2values with respect to the wrist flexionextension, adduction - abduction and grasping forces were 0.79, 0.73 and 0.78 and RMSE were 0.12, 0.17, 0.13 respectively.

This paper focuses on a development of an anthropomorphic robot hand. Human hand is able to dexterously grasp and manipulate various objects with not accurate and sufficient, but inaccurate and scarce information of target objects. In order to realize the ability of human hand, we develop a robot hand and introduce a control scheme for stable grasping by using only kinematic information. The developed anthropomorphic robot hand, KITECH Hand, has one thumb and three fingers. Each of them has 4 DOF and a soft hemispherical finger tip for flexible opposition and rolling on object surfaces. In addition to a thumb and finger, it has a palm module composed the non-slip pad to prevent slip phenomena between the object and palm. The introduced control scheme is a quitely simple based on the principle of virtual work, which consists of transposed Jacobian, joint angular position, and velocity obtained by joint angle measurements. During interaction between the robot hand and an object, the developed robot hand shows compliant grasping motions by the back-drivable characteristics of equipped actuator modules. To validate the feasibility of the developed robot hand and introduced control scheme, collective experiments are carried out with the developed robot hand, KITECH Hand.