• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.119-127
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• 2021

The aim of this paper is to propose a less conservative stabilization condition for leader-following sampled-data control of wheeled mobile robot (WMR) systems by using a clock-dependent Lyapunov function (CDLF) with looped functionals. In the leader-following WMR system, the state and input of the leader robot are measured by digital devices mounted on the following robot, and they are utilized to construct the sampled-data controller of the following robot. To design the sampled-data controller, a stabilization condition is derived by using the CDLF with looped functionals, and formulated in terms of sum of squares (SOS). The considered Lyapunov function is a polynomial form with respect to the clock related to the transmitted sampling instants. As the degree of the Lyapunov function increases, the stabilization condition becomes less conservative. This ensures that the designed controller is able to stabilize the system with a larger maximum sampling interval. The simulation results are provided to demonstrate the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.256-261
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• 2016

An insect-like flapping-wing flying-robot should be able to produce flight forces and control moments at the same time only by flapping wings, because there is no control surface at tail just like an insect. In this paper, design principles for the flapping mechanism and control moment generator are briefly explained, characteristics measured force and moment generations of the robot are presented, and finally controlled flight of the flying robot is demonstrated. The present insect-like robot comprises a lightweight flapping mechanism that can produce a flapping angle larger than $180^{\circ}$ and a control moment generator that produces pitch, roll, and yaw moments by adjusting location of the trailing edges at the wing roots. The measured force and moment data show that the control input angles less than $9^{\circ}$ would not significantly reduce the vertical force generation. It is also observed that the pitch, roll, and yaw control moments are produced only by the corresponding control input. The simple PID control theory is used for the controlled flight of the flying robot, controlling pitch, roll, and yaw motions. The flying robot successfully demonstrated controlled flight for about 40 seconds.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.24-27
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• 2004

This paper describes the method how to control an autonomous robot remotely using Internet. The autonomous robot that has an artificial brain is called "Tarou". (1) It is able to move along the line on the floor based on processing the image data obtained from two CCD cameras. (2) It is able to understand dialogs between human being and it and is able to take actions such as turn right and lefts, go forward 1m and go backward 0.5m, etc. (3) It is able to recognize patterns of objects. (4) It is able to recognize human faces. (5) It is able to communicate human being and to speak according to contents written in the program. We show the techniques to control the autonomous robot "Tarou" remotely by personal computer and/or portable Phone via Internet. The techniques developed in our research could dramatically increase their performance for..the need of artificial life robot as the next generation robot and national homeland security needs.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.381-381
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• 2000

This paper describes the path planning method in an unknown environment for an autonomous mobile robot equipped with CCD(Charge-Coupled Device) camera. The mobile robot moves along the guideline. The CCD camera is useful to detect the existence of a guideline. The wavelet transform is used to find the edge of guideline. Using wavelet transform, we can make an image processing more easily and rapidly. We make a fuzzy control rule using image data then make a decision the position and the navigation of the mobile robot. The center value that indicates the center of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy output. Some actual experiments for the mobile robot applied fuzzy control show that the mobile robot effectively moves to target position.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.433-436
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• 1998

The objective of this paper is to design a adaptive fuzzy controller for autonomous navigation of mobile robot. The adaptive fuzzy controller has an advantage in data processing time and convergence speed. The basic idea of control is to induct membership function and fuzzy inference rules and to scale inducted membership function to suitable robot state. The adaptive fuzzy control method is applied to mobile robot and the simulation results show the effectiveness of our controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2024-2029
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• 2005

In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. In order to achieve high speed and safe navigation, a robot collects environmental information. A robot empirically memorizes locations of high risk due to the abrupt appearance of dynamic obstacles. After collecting sufficient data, a robot navigates in high speed in safe regions. This fact implies that the robot accumulates location dependent environmental information and the robot exploits its experiences in order to improve its navigation performance. This paper proposes a computational scheme how a robot can distinguish regions of high risk. Then, we focus on velocity control in order to achieve high speed navigation. The proposed scheme is experimentally tested in real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation. Although the scope of this paper is limited to the velocity control in order to deal with unexpected obstacles, this paper points out a new direction towards the intelligent behavior control of autonomous robots based on the robot's experience.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.392-397
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• 2020

Unmanned robots are very useful for autonomous security systems. These robots navigate autonomously move in a large area for surveillance. It is very important for robots that cover such a wide area to communicate with a control systems. Therefore, the control system needs various communication methods to check the status of the robot and send/receive messages. In addition, it is necessary to provide an easy interface for the user to send security mission commands to the robot. In this paper, we propose a control system based on a variety of communication techniques to perform security by safely communicating with a number of robots in a wide area space. The proposed system designed for considering user UI, data storage and management, and shows usability by constructing it in a real environment.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.248-255
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• 2013

This paper proposes the architecture of the RILS (Robot-in-the-Loop-Simulation) consisting of the robot, the virtual robot, and the avatar robot which is the type of virtual robots operating according to the robot status and behavior. And the synchronization algorithm for mobilization part of the avatar robot is suggested, which reduces the difference between behaviors of the robot and those of the avatar robot. This difference occurs due to the environmental and mechanical mismatches between the robot and avatar robot. In order to reduce this difference in robots behaviors, the synchronization algorithm controls the avatar robot based on the data observed from the robot's behavior. The proposed architecture and the synchronization algorithm are validated from some simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.921-927
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• 2013

This paper presents a user interface for vision based indirect teaching of a robotic manipulator with Kinect and IMU (Inertial Measurement Unit) sensors. The user interface system is designed to control the manipulator more easily in joint space, Cartesian space and tool frame. We use the skeleton data of the user from Kinect and Wrist-mounted IMU sensors to calculate the user's joint angles and wrist movement for robot control. The interface system proposed in this paper allows the user to teach the manipulator without a pre-programming process. This will improve the teaching time of the robot and eventually enable increased productivity. Simulation and experimental results are presented to verify the performance of the robot control and interface system.