• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.330-333
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• 2005

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.1-8
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• 2002

It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads without any specific marks such as painted guide line or tape. In this method the robot navigates with visual sensors, which uses visual information to navigate itself along the read. The Neural Network System was used to learn driving pattern and decide where to move. In this paper, I will present a vision-based process for AMR(Autonomous Mobile Robot) that is able to navigate on the indoor read with simple computation. We used a single USB-type web camera to construct smaller and cheaper navigation system instead of expensive CCD camera.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.532-532
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• 2000

Conventional artificial intelligence systems are not properly responding under dynamically changing environments. To overcome this problem, reactive planning systems implementing new Al principles, called behavior-based Al or emergent computation, have been proposed and confirmed their usefulness. As another alternative, biological information processing systems may provide many feasible ideas to these problems. Immune system, among these systems, plays important roles to maintain its own system against dynamically changing environments. Therefore, immune system would provide a new paradigm suitable for dynamic problem dealing with unknown environments. In this paper, a new approach to behavior-based Al by paying attention to biological immune system is investigated. The feasibility of this method is confirmed by applying to behavior control of an autonomous mobile robot in cluttered environment.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.355-360
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• 2009

This paper presents mobile robot based down-scale mineral resources exploration test system for the USN (Ubiquitous Sensor Network) based exploration. The system emulates the actual exploration environment. Underneath the metal free test plate, a metal object is attached. A magneto-meter mounted mobile robot runs around on the plate to find the metal. The measured magneto-meter values are transferred to the host PC via wireless network. The system enables to improve the reliability of simulation as well as to help efficient exploration system design. Metal-detecting experiments were carried out to illustrate the efficiency of the proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.585-594
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• 2000

The exact path following of an autonomous mobile robot in a factory and an unreliable environment has many disadvantages in case of a classical control algorithm. In this paper, a neural network control approach based on an error back propagation algorithm is proposed for controlling a mobile robot to follow a line installed on the road. Since not only the three recognized informations from three sensors attached on a mobile robot but also the ten detailed informations in non recognition area are learned with input patterns, a mobile robot moves smoothly an installed line in spite of non perception space. The mobile robot has an effect of error minimization with a short time till a destination. To test an effectiveness of the proposed controller, the two motor velocity changes which is affected from a moving angle change of a mobile robot are simulated with computer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.47-55
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• 2019

The robot is the creation of new markets and various cooperation according to the manufacturing paradigm shift. Cooperative management easy for existing industrial robots, robots work on productivity, manpower to replace the robot in every industry cooperation for the purpose of and demand increases.to exist But the industrial robot at the scene of the cooperation working due to accidents are frequent, threatening the safety of the operator. Of industrial site is configured with a robot in an environment ensuring the safety of the operator to and confidence to communicate that can do the possibility of action.Robot guard system of the need for development cooperation. The robot's cooperation through the sensors and computer vision task within a radius of the double to prevent accidents and accidents should reduce the risk. International protocol for a variety of industrial production equipment and communications opc ua system based on ultrasonic sensors and cnn to (Convolution Neural Network) for video analytics. We suggest the cooperation with the robot guard system. Robots in a proposed system is unsafe situation of workers evaluating the possibility of control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1195-1200
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• 2007

This paper describes indoor location estimation intelligent robot. Indoor location estimation function using RSSI based indoor location estimation system and wireless sensor networks were implemented in the robot. Spartan III(Xilinx, U.S.A.) was used as a main control device in the mobile robot and the current direction data was collected in the indoor location estimation system. The data was transferred to the wireless sensor network node attached to the mobile robot through Zigbee/IEEE 802.15.4, a wireless communication. After receiving it, with the data of magnetic compass the node is aware of and senses the direction the robot head for and the robot moves to its destination. Indoor location estimation intelligent robot is can be moved efficiently and actively without obstacle on flat ground to the appointment position by user.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.82-87
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• 1997

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.74-82
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• 1998

This paper presents a new approach to the design of speed and azimuth control of a mobile robot with two drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the neural-fuzzy network and back propagation algorithm to train the neural-fuzzy network controller in the framework of the specialized learning architecture. It is proposed to a learned controller with two neural-fuzzy networks based on an independent reasoning and a connection net with fixed weights to simplify the neural-fuzzy network. The performance of the proposed controller can be seen by the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2279-2284
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• 2005

Generally, biped walking is difficult to control because it is a nonlinear system with various uncertainties. In this paper, we design a robust control system based on sliding-mode control (SMC) of 5-link biped robot using the wavelet neural network(WNN), in order to improve the efficiency of position tracking performance of biped locomotion. In our control system, the WNN is utilized to estimate uncertain and nonlinear system parameters, where the weights of WNN are trained by adaptive laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified by computer simulations.