• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.214-219
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• 2014

In this paper, a new robot system is designed and manufactured to improve the educational robot. The main processor is realized using the ARM Cortex-M3 and the co-processor is implemented by AVR ATMega2560 to deal with data coming from sensor modules. The processor of sensor modules was developed by the AVR ATMega8. The communication system is composed with IIC communication to alleviate the load of main processor. We have developed the educational robot system adopting the hub module for extension characteristics.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.127-132
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• 2017

In this paper, we propose a controller gain based on model based design and implement the two-wheel inverted pendulum type robot using NXT Lego and RobotC language. Two-wheel inverted pendulum robot consists of NXT mindstorm, servo DC motor with encoder, gyro sensor, and accelerometer sensor. We measurement wheel angle using bulit-in encoder and calculate wheel angle speed using moving average method. Gyro measures body angular velocity and accelerometer measures body pitch angle. We calculate body angle with complementary filter using gyro and accelerometer sensor. The control gain is a weighted value for wheel angle, wheel angular velocity, body pitch angle, and body pich angular velocity, respectively. We experiment and observe the effect of two-wheel inverted pendulum with respect to change of control gains.

• Journal of Sensor Science and Technology
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• v.25 no.2
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• pp.148-154
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• 2016

This paper describes the design and fabrication of a two-axis force/torque sensor and an one-axis force sensor with parallel plate beams(PPSs) for measuring forces and torque in an ankle rehabilitation exercise using by a lower rehabilitation robot. The two-axis force/torque sensor is composed of a Fy force sensor and Tz torque sensor and the force sensor detects x direction force. The two-axis force/torque sensor and one-axis force sensor were designed using by FEM(Finite Element Method), and manufactured using strain-gages. The characteristics experiment of the two-axis force/torque sensor and one-axis force sensor were carried out respectively. As a test results, the interference error of the two-axis force/torque sensor was less than 1.56%, the repeatability error and the non-linearity of the two-axis force/torque sensor were less than 0.03% respectively, and the repeatability error and the non-linearity of the one-axis force sensor were less than 0.03% and 0.02% respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1427-1430
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• 2005

In this paper, the range finder system using a PSD sensor suitable for low-cost localization sensor of a mobile robot. Because the distance-voltage output of a PSD sensor has a non-linear property, the linearizing function is proposed through the experimental characteristics of the sensor. And the characteristics are tested and the distance-voltage data are measured in various colors and materials of object. For a known environment, a mobile robot scans the surroundings using a PSD sensor that can rotate $360^{\circ}$. Finally, the performance and accuracy of the developed system are verified according to the comparison the distance by proposed function with real distance

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.894-899
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• 2008

Measured sensor datum from a quadruped robotics is commonly used for recognizing physical environment information which controls the posture of robotics. We can advance the ambulation with this sensed information and need to synthesize various sensors for obtaining accurate data, but most of these sensors are expensive and require excessive load for the operation. Those defects can be serious problem when it comes to the prototype's practicality and mass production, and maintenance of the system. This paper suggests virtual sensor technology for avoiding previous defects and presents ways to apply a theory to a walking robotics through virtual sensor information which is trained with several kinds of actual sensor information from the prototype system; the general algorithm is initially based on the neural network theory of back propagation. In specific, we verified a possibility of replacing the virtual sensor with the actual one through a reaction force measurement experiment.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.299-308
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• 2011

In this study, we develop a pressure observer to measure the cylinder length of a harbor-construction robot. For the robot control, sensors are required to measure the length of a hydraulic cylinder. The cylinder-position sensor is relatively expensive when the operating environment prohibits external approaches for the measurement of the cylinder position. LVDT or linear scales are usually mounted on the outside of the cylinder, which causes poor durability on a construction site. We use a pressure sensor to indirectly estimate the length of the cylinder. The pressure sensor is mounted inside a hydraulic valve box so that it is protected by the box and easy to waterproof for an underwater robot. By treating oil as a compressible fluid, we derive the nonlinear pressure dynamics as a function of the cylinder position, velocity, and pressure. The recursive least squares (RLS) algorithm is applied to identify the dynamic parameters, and the pressure observer estimates the cylinder position through the pressure acting on the head and the rod of the hydraulic cylinder. The position accuracy is relatively low, but it is acceptable for a construction robot that handles large armor stones.

• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.865-871
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• 2012

This paper presents an observer to estimate the displacement of hydraulic cylinders of an underwater robot for harbour construction using a pressure sensor. In harbour constructing, we place heavy armour stones weighing over 2~3 tons on the surface of the bank to protect it from storming wave. This work typically done by a diver is difficult and dangerous so that we have developed Stone Diver which is the underwater robot for harbour construction. The robot needs a displacement sensors to control the position of hydraulic cylinders. The position sensors mounted outside the cylinders cause poor durability in construction site where shock and dust usually occur. However, the pressure sensor mounted inside a waterproof box improves the durability. Based on the dynamic parameters and the pressures in the cylinder, the observer estimates the cylinder's position. This paper presents the positional accuracy of the pressure based observer and the performance of the underwater robot to assemble the armour stones.