• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.130-140
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• 2011

This paper proposes an optimal posture for the task-oriented movement of dual arm manipulator. A stability criterion function which consists of three kinds of feature-representative parameters has been utilized to define the optimal posture. The first parameter is the force which is applied to the object. The torque of each joint and position of arm are attained from the current sensor and encoder, respectively. From these two data, the applied force to an object is estimated using sum of vectors of the joint torques estimated from the measured current. In order to investigate the robustness of each posture, the variation of the end-effector from the encoder information has been utilized as the second parameter. And for the last parameter for the optimality, the total energy consumption has been used. The total consuming energy of each posture can be computed from the current information and the battery voltage. The proposed robot structure consists of a mobile inverted pendulum and dual manipulators. In order to define the optimal posture for the each object, external disturbances are applied to the mobile inverted pendulum robot and the first and second parameters are investigated to find the optimal posture among the pre-selected most representative postures. Finally, the proposed optimal posture has been verified by the proposed stability criterion function which consists of total force to the object, the fluctuation of the end-effector position, and total energy consumption. The effectiveness of the proposed algorithms has been verified and demonstrated through the practical simulations and real experiments.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.271-282
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• 2003

Automotive occupant packaging has been a part of main ergonomics interests, especially, in terms of driver's posture. Previous research on driver's posture has mainly focused on the initial optimal posture for driving sedans. However, customer preferences on cars are shifting from sedans to RV and automobile manufacturing companies seek to understand temporal changes in drivers' posture according to driving environment. So the main aim of this study was to develop a driver's posture measurement system during driving and investigate casual changes due to duration, car type, traffic flow. Four male drivers participated in the experiments during one week. It was shown that considerable changes in their postures were caused with respect to driving environment, which implies that not only static optimal postures but their dynamic changes should be taken into consideration for proper design and evaluation of interior packaging. The research is expected to help packaging designers understand human drivers so as to improve their comfort.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.108-117
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• 2011

This paper proposes an optimal ARS control of a two-wheel mobile inverted pendulum robot. Conventional researches are highly concentrated on the robust control of a mobile inverted pendulum on the flat ground, $i.e.$, mostly focus on the compensation of gyroscope signals. This newly proposed algorithm deals with a climbing control of a slanted surface based on the dynamic modeling using the conventional structure. During the climbing control of the robot, unexpected disturbance forces are essentially caused by the irregular contact force which comes from the irregular contact angle between the wheel and the terrain. The disturbances have effects on the optimal posture of the mobile robot to compensate the slanted angle. Therefore the dynamics equations through physical interpretation are derived for the selection of optimum climbing posture through ARS. Also using the ultrasonic sensor the slope information is obtained to compensate for the force of gravity. The control inputs are dynamically adjusted to climb up the slanted surface effectively. The proposed algorithm is demonstrated through the real experiments.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.396-398
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• 2009

Scoliosis is a three-dimensional deformity caused by lateral curvature of the spine. The existing braces used to correct the posture were some drawbacks such as inconvenience, tightness as well as unfitness to wear. In this study, we devised a posture guidance system in order to monitor a posture continuously and lead to pose correctly and a new method fur measuring a Cobb's angle value in third dimension based on two 3-axis accelerometers. As a result, the correlation coefficients between desired and measured angles were and standard error between desired and measured angles were 0.99, 1.32(x-axis), 0.99 and 1.10(y-axis), respectively. The devised system showed good potential for the optimal posture guide and an early detection of scoliosis.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.87-93
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• 2019

This research deals with posture optimization for humanoid robot against external forces using genetic algorithm and neural network. When the robot takes a motion to push an object, the torque of each joint is generated by reaction force at the palm. This study aims to optimize the posture of the humanoid robot that will change this torque. This study finds an optimized posture using a genetic algorithm such that torques are evenly distributed over the all joints. Then, a number of different optimized postures are generated from various the reaction forces at the palm. The data is to be used as training data of MLP(Multi-Layer Perceptron) neural network with BP(Back Propagation) learning algorithm. Humanoid robot can find the optimal posture at different reaction forces in real time using the trained neural network include non-training data.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.102-109
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• 2003

Safety and comfort are importance concepts for designers of vehicle seats and instrument panels. There have been a lot of researches on comfortable sitting postures, however, relatively a few researchers have tried to find a desirable driving posture in consideration of both comfort and safety. This study investigates a relationship between comfort and safety of sitting posture of a driver. Since a seat is closely related to comfort, the angular data of comfortable sitting posture were obtained through the correlation between the seat and the driver. In order to acquire the data of safe sitting posture, computer simulations were performed for various seatback angles. Based on comparing and analyzing the data obtained, the optimal sitting posture is suggested for both comfort and safety aspects.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2420-2426
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• 2015

This paper proposes an evolutionary optimization approach for optimal hopping of humanoid robots. In the proposed approach, the hopping trajectory is generated by a central pattern generator (CPG). The CPG is one of the biologically inspired approaches, and it generates rhythmic signals by using neural oscillators. During the hopping motion, the disturbance caused by the ground reaction forces is compensated for by utilizing the sensory feedback in the CPG. Posture control is essential for a stable hopping motion. A posture controller is utilized to maintain the balance of the humanoid robot while hopping. In addition, a compliance controller using a virtual spring-damper model is applied for stable landing. For optimal hopping, the optimization of the hopping motion is formulated as a minimization problem with equality constraints. To solve this problem, two-phase evolutionary programming is employed. The proposed approach is verified through computer simulations using a simulated model of the small-sized humanoid robot platform DARwIn-OP.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.4
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• pp.203-210
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• 2014

In this study, we present a method for correcting unbalanced sitting posture alignment to its optimal position, by designing a chair equipped with pressure sensor. With increasement in sedentary work, such as office work or study, people are now spending more time in chair. To accommodate sedentary life styles, many chairs are being designed for a comfortable sitting condition. However, without awareness and efforts for correct sitting posture, it may not be possible to achieve such condition. When the weight is not distributed evenly while sitting, it may cause various diseases such as scoliosis and a herniated disc. Being inspired by such facts, we have progressed basic researches to maintain the correct sitting posture. To demonstrate the proof-of-concept validation, we installed a series of sensors to a chair and then measured the changes in pressure distribution in various postures. The results show that this approach can be potentially helpful for understanding how fundamental problems due to unbalanced sitting posture can be corrected and maintained properly.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1006-1013
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• 2011

In this paper, we propose an optimal posture control law for an unmanned bicycle by deriving linear bicycle model from fully nonlinear differential equations. We calculate each equilibrium point of a bicycle under any given turning radius and angular speed of rear wheel. There is only one equilibrium point when a bicycle goes straight, while there are a lot of equilibrium points in case of turning. We present an optimal equilibrium point which makes the leaning input minimum when a bicycle is turning. As human riders give rolling torque by moving center of gravity of a body, many previous studies use a movable mass to move center of gravity like humans do. Instead we propose a propeller as a new leaning input which generates rolling torque. The propeller thrust input makes bicycle model simpler and removes input magnitude constraint unlike a movable mass. The proposed controller can hold optimal equilibrium points using both steering input and leaning input. The simulation results on linear control for circular motion are demonstrated to show the validity of the proposed approach.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.113-119
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• 2023

In this paper, we propose an optimization of a pose estimation deep learning model for recognition of abnormal behavior in unmanned stores using radio frequencies. The radio frequency use millimeter wave in the 30 GHz to 300 GHz band. Due to the short wavelength and strong straightness, it is a frequency with less grayness and less interference due to radio absorption on the object. A millimeter wave radar is used to solve the problem of personal information infringement that may occur in conventional CCTV image-based pose estimation. Deep learning-based pose estimation models generally use convolution neural networks. The convolution neural network is a combination of convolution layers and pooling layers of different types, and there are many cases of convolution filter size, number, and convolution operations, and more cases of combining components. Therefore, it is difficult to find the structure and components of the optimal posture estimation model for input data. Compared with conventional millimeter wave-based posture estimation studies, it is possible to explore the structure and components of the optimal posture estimation model for input data using genetic algorithms, and the performance of optimizing the proposed posture estimation model is excellent. Data are collected for actual unmanned stores, and point cloud data and three-dimensional keypoint information of Kinect Azure are collected using millimeter wave radar for collapse and property damage occurring in unmanned stores. As a result of the experiment, it was confirmed that the error was moored compared to the conventional posture estimation model.