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Development of Rehabilitation Robot Systems for Ambulatory Recovery
이춘영(Choon-Young Lee) 대한기계학회 2005 대한기계학회 춘추학술대회 Vol.2005 No.4
This paper presents a mobile gait training system with body weight support (BWS), which relieves the patient of body weight of a prescribed amount by supporting the subject with a harness. The system is based on electrical motors to achieve system mobility according to the subject's motion of walking while it maintains a constant force on the body based on pneumatic actuators. The mobility of the system seems to be important for a correct gait pattern since the subject is able to walk on the ground actually. The system has a simple architecture to construct, and is practical to the gait rehabilitation.
색채선별기 곡물 이미지 가시화 및 선별기법에 관한 연구
이춘영(Choon-Young Lee),얀레이(Lei Yan),이상룡(Sang-Ryong Lee),박철우(Cheol-Woo Par) 한국가시화정보학회 2008 한국가시화정보학회지 Vol.6 No.2
The color sorting technique utilizing the image processing method is very applicable tool to analyze motion of a free-falling object in many agricultural and industrial research fields. In the present study, we have developed an image processing system and algorithm to sort good quality rice grains effectively from the bad ones. The system employs a high speed rate line-scan CCD camera with 2K-pixels and worked with a high speed DSP and FPGA in-line. It can accumulate acquired line-scan image data and visualize each grain image clearly. As a result, we can easily calculate the number of pixels occupied by grain(=grain size), gray level and its correct position by visualizing grain images rapidly.
상지 외골격 로봇 제어를 위한 인체 팔 동작의 기구학 및 동역핮거 분석
김현철(Hyunchul Kim),이춘영(Choon-Young Lee) 제어로봇시스템학회 2012 제어·로봇·시스템학회 논문지 Vol.18 No.12
To achieve synchronized motion between a wearable robot and a human user, the redundancy must be resolved in the same manner by both systems. According to the seven DOF (Degrees of Freedom) human arm model composed of the shoulder, elbow, and wrist joints, positioning and orientating the wrist in space is a task requiring only six DOFs. Due to this redundancy, a given task can be completed by multiple arm configurations, and thus there exists no unique mathematical solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and their effect on the redundancy resolution of the human arm based on a seven DOF manipulator model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing different cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid for the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each two consecutive points along the task space trajectory. As a first step, the redundancy based on the kinematic criterion will be thoroughly studied based on the motion capture data analysis. Experimental results indicate that by using the proposed redundancy resolution criterion in the kinematic level, error between the predicted and the actual swivel angle acquired from the motor control system is less than five degrees.
상지 외골격 로봇 제어를 위한 인체 팔 동작의 기구학 및 동역학적 분석 - 파트 2 : 제한조건의 선형 결합
김현철(Hyunchul Kim),이춘영(Choon-Young Lee) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.8
The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.
이상룡,허근섭,강오현,이춘영,Lee, Sang-Ryong,Heo, Geun-Sub,Kang, Oh-Hyun,Lee, Choon-Young 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.3
In this paper, we proposed a technique to recognize three states in stance phase of gait cycle. Walking assistive devices are used to help the elderly people walk or to monitor walking behavior of the disabled persons. For the effective assistance, they adopt an intelligent sensor system to understand user's current state in walking. There are three states in stance phase; Loading Response, Midstance, and Terminal Stance. We developed a foot pressure sensor using 24 FSRs (Force Sensing/Sensitive Resistors). The foot pressure patterns were integrated through the interpolation of FSR cell array. The pressure patterns were processed to get the trajectories of COM (Center of Mass). Using the trajectories of COM of foot pressure, we can recognize the three states of stance phase. The experimental results show the effective recognition of stance phase and the possibility of usage on the walking assistive device for better control and/or foot pressure monitoring.