• Biomaterials and Biomechanics in Bioengineering
• /
• 제2권4호
• /
• pp.207-223
• /
• 2015

In this paper a method for simultaneous swift non-linear analysis and optimal design/posture of mechanical/biomechanical systems is presented. The method is developed to get advantages of iterations in non-linear analysis and/or generations in genetic algorithm (GA) for the purpose of efficient analysis within the optimal design/posture. The method is applicable for both size and geometry optimizations wherein material and geometry non-linearity are present. In addition to established mechanical systems, the method can solve biomechanical models of human musculoskeletal system. Optimization-based procedures are popular methods for resolving the redundancy at joints wherein the number of unknown muscle forces is far more than the number of equilibrium equations. These procedures involve optimization of a cost function(s) which is assumed to be consistent with the central nervous system's strategy when activating muscles to assure equilibrium. However, because of the complexity of biomechanical problems (i.e., due to non-linear biomaterial, large deformation, redundancy of the problem and so on) efficient analysis are required within optimization procedures as suggested in this paper.

• 한국정밀공학회지
• /
• 제19권4호
• /
• pp.187-194
• /
• 2002

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During talc motion, if there exists no obstacle, the end-effector of the robot arm moves along the predefined path. But if these exists an obstacle and close to talc robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture far collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sites of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
• /
• pp.147-150
• /
• 1996

Human posture prediction and motion simulation methods try to solve inverse kinematic problems using the optimization technique based on the concept of minimum principle. It is very important to select a cost function which relfects the human posture acurately. In this study, lifting postures were predicted using the five biomechanical cost functions and compared with real human postures in order to evaluate the predictivities of the cost functions. The result showed that all the biomechanical cost functions used in this study could not predict lifting postures accurately. The cost function which minimizes the sum of joint moments showed the smallest mean prediction error, while the one which minimizes the MUR showed statistically better performance.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2009년도 추계학술대회 논문집
• /
• pp.647-648
• /
• 2009

• 대한인간공학회지
• /
• 제13권2호
• /
• pp.65-79
• /
• 1994

A biomechanical model of lower extremity in seated postures was developed to assess muscular activities of lower extremity involved in a variety of foot pedal operations. The model incorporated four rigid body segments with the twenty-four muscles to represent lower extremity. This study deals with quasi-static movement to investigate dymanic movement effect in seated foot operation. It is found that optimization method which has been used for modeling the articulated body segments does not predict the forces generated from biarticular muscles and antagonistic muscles reasonably. So, the revised nonlinear optimization scheme was employed to consider the synergistic effects of biarticular muscles and the antagonistic muscle effects from the stabilization of the joint. For the model validation, three male subjects performen the experiments in which EMG activities of the nine lower extremity muscles were measured. Predicted muscle forces were compared with the corresponding EMG amplitudes and it showed no statistical difference. For the selection of optimal seated posture, a physiological meaningful criterion for muscular load sharing developed.

• 한국정밀공학회지
• /
• 제15권8호
• /
• pp.165-173
• /
• 1998

In this paper, a motion control algorithm is developed by using fuzzy control technique, which makes a robot arm avoid unexpected obstacles when the robot is moving from the start to a goal posture. During the motion, if there exist no obstacles the robot arm moves along the pre-defined path. But if some obstacles are recognized and close to the robot arm, a fuzzy controller is activated to adjust the path of the robot arm. To show the feasibility of the developed algorithm, numerical simulations and experiments are carried out. In the experiments, redundant planar robot arms are considered for the collision avoidance test, and it was proved that the developed algorithm gives good collision avoiding performance.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
• /
• pp.358-363
• /
• 1992

A two-dimensional static biomechanical model of lower extremity in the seated posture was developed to assess muscular activities of lower extremity required for a variety of foot pedal operations. Muscle forces of the model were predicted using the double linear optimization scheme. For the model validation, three subjects performed the experiments which measured EMG activities of six lower extremity muscles. Predicted muscle forces were compared with the corresponding rectified intergrated EMG amplitudes and it showed reasonable results.

• 제어로봇시스템학회논문지
• /
• 제5권3호
• /
• pp.249-256
• /
• 1999

The conventional robot manipulability is decomposed into linear manipulability and angular manipulability so that they may be analysed and visualized in easy way even in the case of 3 dimensional task space with 6 variables. After the Jacobian matrix is decomposed into linear part and angular part, constraint on joint velocities is transformed into linear task velocity and angular task velocity through the decomposed Jacobian matrices. Under the assumption of redundant robot manipulators, several optimization problems which utilize the redundancy are formulated to be solved by linear programming technique or sequential quadratic programming technique. After deriving the solutions of the optimization problems, we give graphical interpretations for the solutions.

• 대한인간공학회지
• /
• 제11권1호
• /
• pp.81-92
• /
• 1992

A two-dimensional static biochemical model of lower extremity in the seated posture was developed to assess muscular activities of lower extremity required for a variety of foot pedal operations. We found that the double linear optimization method that has been used for modelling articulated body segments does no predict the forces generated by biarticular muscles reasonably, so the revised double linear optimization scheme was used to consider the synergistic effects of biarticular muscles in our model, assuming that the muscle forces are distributed proportionally based on their physiological cross sectional area. The model incorporated three rigid body se- gments with six muscles to represnet lower extremity. For the model validation, three male subjects performed the experiments in which EMG activities of six lower extremity muscles were measured. Predicted muscle forces were compare with the corresponding EMG amplitudes and it showed no statistical difference. The model being developed can be used to design and assess pedal and foot-related tool design.

• 제어로봇시스템학회논문지
• /
• 제18권4호
• /
• pp.353-358
• /
• 2012

Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method is also important as well as its accuracy. In this paper, we propose unified detection and tracking method for humans using Gaussian-PSO (Gaussian Particle Swarm Optimization) with the HOG (Histograms of Oriented Gradients) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking.