• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.364-371
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• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.368-371
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• 2003

A new accurate and reliable human-in-the-loop control by artificial neural network (ANN) for human assistance robot was proposed in this paper. The principle of human-in-the-loop control by ANN was explained including the system architecture of human assistance robot control the design of the controller the control process as well as the switching of the different control patterns. Based on the proposed method, the control of meal assistance robot was implemented. In the controller of meal assistance robote a feedforward ANN controller was designed for the accurate position control. For safety a feedback ANN forcefree control was installed in the meal assistance robot. Both controllers have taken fully into account the influence of human arm upon the meal assistance robote and they can be switched smoothly based on the external force induced by the challenged person arm. By the experimental and simulation work of this method for an actual meal assistance robote the effectiveness of the proposed method was verified.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.622-628
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• 2013

This paper describes the development of a thigh-muscle strength-assistance robot, which is a kind of wearable robot. For practicality and commercialization, we proposed three fundamental concepts: the reduction of the thigh-muscle strength, minimized degree of dependence on a powered actuator, and complete wearer safety. Based on these concepts, a spring and link bar mechanism was conceived as a novel idea. The movement of the thigh is transferred to the spring mechanism through the link bar; hence, the elastic force of the spring assists the thigh muscle. Using forse sensing resistor (FSR) sensors and a powered cam mechanism, the muscle assistance is automatically activated and deactivated according to the wearer's movement. The specific mechanisms of the robot are addressed in detail, and the effectiveness is verified by experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.35-36
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• 2007

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2376-2383
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• 2015

Assistance of the operator’s walking ability while carrying a load is a challenging area in lower limb exoskeletons. We implement an exoskeleton called the Unmanned Technology Research Center Exoskeleton (UTRCEXO), which enables the operator to walk with a load more comfortably. The UTRCEXO makes use of two types of DC motor to assist the hip and knee joints. The UTRCEXO detects the operator’s walking intention including step initiation with insole-type FSRs faster without using any bio-signals and precedes the operator’s step with a reference torque. It not only reduces interaction forces between the operator and the UTRCEXO, but also allows the operator to walk with a load more comfortably. In this paper, we present the UTRCEXO implementing the walking assistance mechanism with interaction force reduction during walking.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.37-38
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• 2008

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.447-456
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• 1997

When the disabled is operating a rehabilitation assisting system with a joystick by himself, unlike in the case of a normal person, tremor with joystick control or instant miscontrol can often occur. If these misoperations should be directly relayed to the system, shaking or malfunction of the mobile rehabilitation assisting system might be the result. The safety of the disabled is of prime concern. To solve this problem, that is, to prevent the miscontrol of the disabled operator and avoid crashes into his or her surroundings, we propose the force-reflection locomotion algorithm with the joystick. This method uses ultrasonic sensors to measure the distance between the object and mobile robot. Based on the reception of sensory data, the necessary torque is applied via the joystick to the attatched motor. To confirm the effectiveness of the proposed method, the subjects on the reflected force by the dynamic characteristics of the joystick and the reflected force by the distance information are tested Even though there are some differences in human dexterity, we confirmed the fact that the information from the obstacles was relayed to the operator via the joystick and resulted in an improved operational performance and safety level with regard to those obstacles.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.3
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• pp.141-146
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• 2008

The purpose of this study is to develop the algorithm which can control muscle power assist robot especially for elderly. Recently, wearable robots for power assistance are developed by many researchers, and its application fields are also variable such as for medical or military equipment. However, there are many technical barriers to develop the wearable robot. This study suggest a control method improving performance of a wearable robot system by using a EMG signal of major muscles and a force sensor signal as command signal of system. The result of the robot Prototype efficiency experiment, the case of Maximum Isometric motion it suggest 100% power of muscle, the man need only 66% of MVIC(Maximum Voluntary Isometric Contraction) to lift 5kg dumbbell without robot assist. However the man needs only 52% of MVIC to lift 5kg dumbbell with robot assist. Therefore 20% muscle power increased with robot assist. Also, we designed light weight robot mechanism that extract the command signal verified and drive the wanted motions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.2
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• pp.215-221
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• 2010

Korea has recently joined the Development Assistance Committee (DAC) and currently implements a policy of vastly expanding the size of ODA. Indonesia has highly possessed growth potential in terms of vast quantity of natural resources, cheap labor force, and large local markets. Researches on how to support the Special Territory of Aceh province were made in this study. There is a necessity to increase the capacity of matter to the fishermen, and support facilities and infrastructure assistance to support the safety system in the sea.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.209-215
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• 2019

In order to provide a safe free-weight-training environment to people without workout trainers, we suggest a smart bench press machine with an automatic weight control system sensitive to user tiredness. Physical weight plates on the machine are replaced with a hydraulic cylinder as a press load and the cylinder knob is coupled with a step motor to change its tensile force automatically in-between lifting exercises. Three subjects participated to verify the usability of the smart bench press machine. They were asked to lift a 6-RM press load 10 times with 3 different lifting conditions: 1) no assistance, 2) a human assistance, and 3) the automatic weight control. All subjects were not able to complete the 10 sets without assistance due to tiredness, but they finished the full sets under the two assistive conditions. Average lifting speeds under the automatic weight control condition showed the most consistent level. Normalized quasi-tension data based on surface electromyogram signals of both Pectoralis Majors revealed that the subjects maintained the target muscle activation level above 50% but not more than 80% throughout the 10 sets. Therefore, the smart bench press machine is expected to both keep pace with the lifting exercise and reduce risk of injuries due to excessive muscle tensions.