• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1756-1763
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• 2011

This paper was researched the straight cruise of fish robot according to biological mimic, and it was compared the proposed method which was considered up to 7th order components in fourier series of Liu's tail motion function with the approximate method which was used general sine function by simulation. If fish robot has a large number of links and if the length of tail link is long. The end rotary joint trajectory of tail motion function generally is different from sine function. Therefore The approximate method which expresses tail motion trajectories as fundamental component in fourier series has a problem. Through the computer simulation, the proposed method showed 10% excellent propulsion and velocity than the conventional method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.417-420
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• 1987

For an increased level of productivity, it is important that the end-point of a robot manipulator moves from an initial location to final position in the minimum time subject to the available maximum actuator's torque (or force) at each joints. The main issue is to develop an algorithm to compute the actuators in real-time. In this paper, a digital state feedback control algorithm has bean developed to obtain the near-minimum-time trajectory for the end-effector of a robot manipulator. In this algorithm, the poles of the linearized closed loop system are judiciously placed in the Z-plane to permit minimum-time response without violating the constraints on the actuator torques. The validity of this algorithm have been established using numerical simulations. A three-link manipulator in chosen for this purpose and results are discussed for three different combinations of initial and final station.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.217-227
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• 1996

The new filed of learning control develops controllers that learn to improve their performance at executing a given task , based on experience performing this specific task. In a previous work[6], authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper develops improved indirect learning control algorithms, and studies the use of such controller indecentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an asssembly line. This paper starts with decentralized discrete time systems. and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The resultof the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample tie in the digital learning controller is sufficiently short.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.8 s.227
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• pp.1075-1086
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• 2004

In this paper, Time Delay Control(TDC) for robot manipulators is analyzed and its problems are founded. In order to remedy the problems, the enhanced controller is proposed and analyzed. The effect of friction associated with TDC is reported and its cause is presented. Through the analysis, simulation and experiment, it is shown that the friction effect causes serious degradation in control performance and that it is a result of the error of Time Delay Estimation(TDE) in TDC. In order to remedy the problems, TDC combined with Internal Model Control(IMC) concept is proposed. The proposed compensator is effective enough to handle the bad effect of friction, and is so simple and efficient as to match positive attribute of TDC. The simulation and experimental results show the effectiveness of proposed controller against the friction of the robot manipulators.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.87-93
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• 2019

This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1043-1050
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• 2013

Parallel robots used in industry require high stiffness or high speed because of their structural characteristics. Nowadays, the importance of rapid transportation has increased in the distribution industry. In this light, an industrial parallel robot has been developed for high-speed transfer. The developed parallel robot can handle a maximum payload of 3 kg. For a payload of 0.1 kg, the trajectory cycle time is 0.3 s (come and go), and the maximum velocity is 4.5 m/s (pick amp, place work, adept cycle). In this motion, its maximum acceleration is very high and reaches approximately 13g. In this paper, the design, analysis, and performance test results of the developed parallel robot system are introduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.901-906
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• 2007

Algorithms of path planning and obstacle avoidance are essential to autonomous mobile robots that are working in unknown environments in the real time. This paper presents a new navigation algorithm for an autonomous mobile robot with vision and IR sensors using fuzzy rules. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. In this approach, several digital image processing technique is employed to detect edge of obstacles and the distances between the mobile robot and the obstacles are measured. An autonomous mobile robot with single vision and IR sensors is built up for experiments. We also show that the autonomous mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.173-178
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• 2017

As research on the practical use of robots has continued since the past, advancements into each field of society are being continuously tried in modern society, breaking bounds from the previous experimental environment. However, in order for robots to be applied to the real environment, the production cost, which is considered to be the biggest disadvantage of commercializing the existing robot platform, and the adaptability issue in working environments in terms of human standards must be considered. This paper proposes a robot of biped walking form, which conforms to the degree of freedom and the size of human beings. By replacing the encoder with a combined module of potentiometer, the high cost of production is reduced, and by adopting a modular design that is easy to replace parts, the maintenance cost of robots is reduced. Finally, stability was verified by applying a walking pattern to two dummy robots of different sizes and motor arrangements. In this paper, after developing the real biped walking robots, the performance and usability were verified through walking experiments and applying the walking pattern using the developed robots.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.305-311
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• 2012

In this paper, we propose a gait generation method for quadruped robots using the xz-axis sway of the quadruped robot, which minimizes the shake of the quadruped robot and maximizes the stability margin. In the proposed method, the gait is generated based on wave gaits and the stability analysis uses the body tilt information of the quadruped robot according to the leg's height of leg. In addition, to reduce the impact on the body caused by the z-axis sway while walking, the proposed method generates the smooth walking movement trajectory with less impact by using Fourier series. Finally, to verify the applicability and effectiveness of the proposed method, we carry out the computer simulations and the real walking experiments with the implemented quadruped robot.