• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.3
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• pp.143-150
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• 2012

In this paper, we introduce an intelligent quadruped walking robot that can perform stable walking and a couple of intelligent behaviors. The developed robot has two sets of ultrasonic sensors and six sets of infrared sensors and can perform obstacle avoidance by detecting obstacles and estimating the distances and directions of those obstacles. The robot also has a stereo camera and can paly soccer by detecting a ball and estimating the 3 dimensional coordinates of the ball. In performing those intelligent behaviors, the robot needs to have the capability of generating its walking patterns, solving the inverse kinematics problem, and interfacing several sensors in realtime. Therefore we designed a hierarchical controller that consists of a main controller and an auxiliary controller. The main controller is a 32-bit DSP that can perform fast floating-point opertaion and the auxiliary one is a 8-bit micro-controller. We showed that the developed quadruped walking robot successfully perform those intelligent behaviors through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1105-1108
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• 2003

The micro robot soccer playing system is introduced. Studying and learning, evolving in artificial agents are very difficult problem, but on the other hand we think more powerfully challenging task. In our laboratory, this soccer-system studies mainly centered on single agent learning problem. The construction of such experimental system has involved lots of kinds of challenges such as robot designing, vision processing, motion controlling. At last we will give some results showing that the proposed approach is feasible to guide the design of common agents system.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.195-201
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• 2010

Recently, the necessity of the autonomous mobile robot is emphasized in order to enlarge the scope of activity and actively cope with the change of work environment. This paper proposes the algorithm which enables the mobile robot to avoid obstacles and lead it to the destination by the shortest path. And we verify the usability by a simulation. We made the algorithm with micro-GA and $\lambda$-geometry MRA. The area of simulation is limited to 320(width)$\times$200(length) pixels and one pixel is one centimeter. When we planned the path with only $\lambda$-geometry MRA, we could find the direction for path planning but could not find the shortest path. But when we planned the path with $\lambda$-geometry MRA and micro-GA, we could find the shortest path. So the algorithm enables us to find the direction for path planning and the shortest path.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1823-1824
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• 2008

We propose a remote controlled robot manipulator using force feedback joystick. User can control easily 5 d.o.f robot manipulator in 3 demensional space using general joystick. A force sensor attached in developed gripper sends signal to main robot controller so as to know gripper grasp the object. The signal also sent to user through force feedback joystick. We designed a dexterous 5 d.o.f robot manipulator analysis the kinematics and inverse kinematics. The robot was simply developed using serial RC motor. As a main robot controller, we use 32bit MPU(AT91SAM7256) and micro C/OS. To show the validity of our developed robot, a several experiments were demonstrated.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.141-147
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• 2003

This paper represents an absolute positioning system using a light navigation path for mobile robot. The absolute positioning system is composed of the projector unit which generates a laser beam using laser diode and mobile robot with the optical detector which has some optical sensors. The projector unit is fixed over the navigating plane of mobile robot to generate the light navigation path, and the optical detector located upper part of mobile robot detects the generated laser beam from the projector. The navigation of mobile robot is controlled by the micro-processor which compares the detected present position from the detector with the previously programmed navigation path. And experimental results show that our sensor system can be used for the absolute positioning system of the mobile robot.

• International Journal of Safety
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• v.7 no.1
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• pp.1-4
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• 2008

Application of the Microsoft robotics studio (MSRS) to the design of a factory safety monitoring robot is presented. Basic structures of the MSRS and the service are introduced. The service is the key building block of the MSRS. Control of the safety monitoring robot is performed using four basic services: 1) the robot service which communicates with the embedded micro-processor and other services, 2) the sensor service that notifies the subscribing services of the change of the sensor value, 3) the motor service which controls the power levels to the motors, 4) the drive service which maneuvers the robot. With built-in capabilities of the MSRS, control of factory safety monitoring robot can be more easily performed.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.551-558
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• 2008

This paper deals with the real-time stable walking for a humanoid robot, ISHURO-II, on uneven terrain. A humanoid robot necessitates achieving posture stabilization since it has basic problems such as structural instability. In this paper, a stabilization algorithm is proposed using the ground reaction forces, which are measured using FSR (Force Sensing Resistor) sensors during walking, and the ground conditions are estimated from these data. From this information the robot selects the proper motion pattern and overcomes ground irregularities effectively. In order to generate the proper reaction under the various ground situations, a fuzzy algorithm is applied in finding the proper angle of the joint. The performance of the proposed algorithm is verified by simulation and walking experiments on a 24-DOFs humanoid robot, ISHURO-II.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.162-169
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• 1999

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.399-400
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• 2013