• Advances in robotics research
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• v.2 no.2
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• pp.113-127
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• 2018

Robotics and automation are rapidly growing in the industries replacing human labor. The idea of robots replacing humans is positively influencing the business thereby increasing its scope of research. This paper discusses the development of an experimental platform controlled by a robotic arm through Robot Operating System (ROS). ROS is an open source platform over an existing operating system providing various types of robots with advanced capabilities from an operating system to low-level control. We aim in this work to control a 7-DOF manipulator arm (Robai Cyton Gamma 300) equipped with an external vision camera system through ROS and demonstrate the task of balancing a ball on a plate-type end effector. In order to perform feedback control of the balancing task, the ball is designed to be tracked using a camera (Sony PlayStation Eye) through a tracking algorithm written in C++ using OpenCV libraries. The joint actuators of the robot are servo motors (Dynamixel) and these motors are directly controlled through a low-level control algorithm. To simplify the control, the system is modeled such that the plate has two-axis linearized motion. The developed system along with the proposed approaches could be used for more complicated tasks requiring more number of joint control as well as for a testbed for students to learn ROS with control theories in robotics.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.295-304
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• 2000

In the teleoperation system, force and velocity signals are communicated between a master and a slave robot. The addition of force feedback to a teleoperation system benefits the operator by providing more information to perform given tasks especially for tasks requiring contact with environment. When the master and slave arms are located in different places, time delay is unavoidable and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The control scheme proposed in this paper is based on the estimator with virtual master model. Delayed signal from the master robot can be replaced by the estimated signal with the virtual master model. This control scheme makes the teleoperation system stable for the given time delay while the conventional scheme is not. This new control scheme is verified through numerical simulations and an experiments using the dual axis testbed of the teleoperation system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.58-69
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• 2014

This paper proposes a method for predicting maximum friction coefficients and optimal slip ratios as optimal control parameters for traction control or slip control of autonomous mobile robots on rough terrain. This paper focuses on strength of ground surface which indicates different characteristics depending on material types on surface. Strength of various material types can be estimated by Willoughby sinkage model and by a developed testbed which can measure forces, velocities, and displacements generated by wheel-terrain interaction. Estimated strength is collaborated on building improved Brixius model with friction-slip data from experiments with the testbed over sand and grass material. Improved Brixius model covers widespread material types in outdoor environments on predicting friction-slip characteristics depending on strength of ground surface. Thus, a prediction model for obtaining optimal control parameters is derived by partial differentiation of the improved Brixius model with respect to slip. This prediction model can be applied to autonomous mobile robots and finally gives secure maneuverability on rough terrain. Proposed method is verified by various experiments under similar conditions with the ones for real outdoor robots.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.231-240
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• 2023

It remains a challenge for robots to learn avoiding obstacles automatically in path planning using deep reinforcement learning (DRL). More and more researchers use DRL to train a robot in a simulated environment and verify the possibility of DRL to achieve automatic obstacle avoidance. Due to the influence factors of different environments robots and sensors, it is rare to realize automatic obstacle avoidance of robots in real scenarios. In order to learn automatic path planning by avoiding obstacles in the actual scene we designed a simple Testbed with the wall and the obstacle and had a camera on the robot. The robot's goal is to get from the start point to the end point without hitting the wall as soon as possible. For the robot to learn to avoid the wall and obstacle we propose to use the double deep Q networks (DDQN) to verify the possibility of DRL in automatic obstacle avoidance. In the experiment the robot used is Jetbot, and it can be applied to some robot task scenarios that require obstacle avoidance in automated path planning.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.35-44
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• 2020

In this study, we propose a reliable command placement recognition algorithm using tangible commands blocks developed for our coding puzzle platform, and present its performance measurement results on an Augmented Reality testbed environment. As a result, it can recognize up to 30 tangible blocks simultaneously and their placements within 5 seconds reliably. It is successfully ported to an existing coding puzzle mobile app and can operate an IoT attached robot via bluetooth connected mobile app.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2930-2932
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• 2000

In this paper. a robust gesture recognition system is designed and implemented to explore the communication methods between human and computer. Hand gestures in the proposed approach are used to communicate with a computer for actions of a high degree of freedom. The user does not need to wear any cumbersome devices like cyber-gloves. No assumption is made on whether the user is wearing any ornaments and whether the user is using the left or right hand gestures. Image segmentation based upon the skin-color and a shape analysis based upon the invariant moments are combined. The features are extracted and used for input vectors to a radial basis function networks(RBFN). Our "Puppy" robot is employed as a testbed. Preliminary results on a set of gestures show recognition rates of about 87% on the a real-time implementation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.147-155
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• 2015

In this paper, we consider a mobile sensor network for monitoring a polluted area where human beings cannot access. Due to the limited sensing range of individual unmanned vehicles, they need to cooperate to achieve an effective sensing coverage and move to a more polluted region. In order to address the limitations of sensing and communication ranges, we propose a hazardous substance monitoring network based on virtual force algorithms, and develop a testbed. In the considered monitoring network, each unmanned vehicle achieves an optimal coverage and move to the highest interest area based on neighboring nodes sensing values and locations. By using experiments based on the developed testbed, we show that the proposed monitoring network can autonomously move toward a more polluted area and obtain a high weighted coverage.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.298-311
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• 2015

Nowadays, automatic digging operation of an excavator is a big challenge due to the complexity of digging environment, the hardness of soil and buried obstacles into the ground. In order to achieve the maximum soil bucket volume, this paper introduces a novel engineering model that was developed as a virtual excavator in the design phase. Through this model, the designs of mechanical and control systems for autonomous excavator are executed and modified easily before developing in real testbed. Based on a concept of an autonomous excavation, a mechanical system of excavator was first designed in SOLIDWORKS, and a soil model also was modeled by finite-element analysis in ANSYS, both modeled models were then exported to ADAMS environment to investigate the digging behavior through virtual simulation. An intelligent control strategy was generated in MATLAB/Simulink to control the excavator operation. The simulation results were demonstrated by effectiveness of the proposed excavator robot in testing scenarios with many soil types and obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.176-182
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• 2011

Industrial network, often referred to as fieldbus, becomes an indispensable component for intelligent manufacturing systems. Thus, in order to satisfy the real-time requirements of field devices such as sensors, actuators, and controllers, numerous fieldbus protocols have been developed. But, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multi-vendor products. As an alternative to fieldbus, the Ethernet (IEEE 802.3) technology is being adapted to the industrial environment. However, the crucial technical obstacle of Ethernet is its non-deterministic behavior that cannot satisfy the real-time requirements. Recently, the EtherCAT protocol becomes a very promising alternative for real-time industrial application due to the elimination of uncertainties in Ethernet. This paper focuses on the implementation of the IEC 61800 based real-time EtherCAT network for multi-axis smart driver. To demonstrate the feasibility of the implemented EtherCAT slave module, its synchronization performance is evaluated on the experimental EtherCAT testbed with a single axis smart driver.