• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.532-539
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• 2001

In robot teleoperation, much research has been carried out to control the slave robot from remote site. One of the essential devices for robot teleoperation is the masterarm, which is a path command generating device worn on human arm. In this paper, a new masterarm based on human kinematics is proposed. Its controller is based on the distributed controller architecture composed of two controller parts: a host controller and a set of satellite controllers. Each satellite controller measures the corresponding joint angle, while the host controller performs forward and inverse kinematics calculation. This distributed controller architecture can make the data updating faster, which allows to implement real-time implementation. The host controller and the satellited controllers are networked via three-wire daisy-chained SPI(Serial Peripheral Interface) protocol, so this architecture makes the electrical wiring very simple, and enhances maintenance. Analytical method for finding three additional unknown joint angles is derived using only three measured angles for each shoulder and wrist, which makes th hardware implementation very simple by minimizing the required number of satellite controllers. Finally, the simulation and experiment results are given to demonstrate the usefulness and performance of the proposed masterarm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.93-100
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• 2007

The mobile robots to rescue a life in a disaster area and to explore planets demand high mobility as well as recognition of the environment. To avoid unknown obstacles exactly in unknown environment, accurate sensing is required. This paper proposes a sensor fusion to recognize unknown obstacles accurately by using low-cost sensors. Ultrasonic sensors and infrared sensors are used in this paper to avoid obstacles. If only one of these sensors is used alone, it is not useful fer the mobile robots to complete their tasks in the real world since the surrounding environment in the real world is complex and composed of many kinds of materials. So infrared sensor may not recognize transparent or reflective obstacles and ultrasonic sensor may not recognize narrow obstacles, far example, columns of small diameter. Therefore, I selected six ultrasonic sensors and five infrared sensors to detect obstacles. Then, I fused ultrasonic sensors with infrared sensors in order that both advantages and disadvantages of each sensor are utilized together. In fusing sensors, fuzzy algorithm is used to cope with the uncertainties of each sensor. TAMRY which is terrain-adaptive mobile robot is used as the mobile robot for experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1122-1131
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• 2012

This paper presents obstacle avoidance method for scout robot or industrial robot in unknown environment by using IR sensor and vision system. In the proposed method, robots share the information where the obstacles are located in real-time, thus the robots can choose the best path for obstacle avoidance. Using IR sensor and vision system, multiple robots efficiently evade the obstacles by the proposed cooperation method. No landmark is used at wall or floor in experiment environment. The obstacles don't have specific color or shape. To get the information of the obstacle, vision system extracts the obstacle coordinate by using an image labeling method. The information obtained by IR sensor is about the obstacle range and the locomotion direction to decide the optimal path for avoiding obstacle. The experiment was conducted in $7m{\times}7m$ indoor environment with two-wheeled mobile robots. It is shown that multiple robots efficiently move along the optimal path in cooperation with each other in the space where obstacles are located.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.4
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• pp.85-102
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• 1990

Up to now, most robot control systems are very naive. They consist of a number of independent position-servo loops to control each joint angle separately. Those control systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severely limited in range of application, speed of operation and variation of payload. This study proposed a new method to design a robot manipulator controller capable of tracking the reference trajectories of joint angles in a reasonable accuracy to cope with actual situations of varying payload, uncertain parameters. The adaptive model following control method has been used to improve existing robot manipulator controllers. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the designer. The stability of adaptive controller is based on the Second Method of Lyapunov. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance under various load varia- tion and parameter uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.521-525
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• 2011

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.933-938
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• 2010

In this paper, we propose the organization of a sensor system and user's intent detection algorithm for walking assist rehabilitation robots. The main purpose of walking assist rehabilitation robots is assisting SCI patients to walk in normal environment. To use walking assist rehabilitation robot in normal environment, it is needed to consider various factors about user's safety and detection of user's intent and so on. For these purposes, we have analyzed the use case of rehabilitation robots and organized the system of sensors for walking assist rehabilitation robots and finally, we have developed the algorithm which is used to detect user's intent for those. We applied our proposal method in the rehabilitation robot, ROBIN, and verified their effectiveness by normal, not patient.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.157-162
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• 2005

This paper presents an adaptive compensator using the fuzzy systems for robot manipulator with unknown frictions. In general, frictions are neglected or dynamic frictions are only considered in robot control theories. The proposed control method considers viscous frictions as well as dynamic frictions. Using the property that the frictions of joints are decoupled, SISO-fuzzy systems are utilized to approximate each friction. The stability of overall control system is proven and the adaptive laws are derived based on Lyapunov stability theorey. To verify the validity of the proposed control strategy, the results of computer simulations are shown for 2-link robot manipulator. The ability of approximating of the fuzzy system is also shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.259-263
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• 2008

The dynamics of mobile robot is nonlinear. To cope with this nonlinearity, many advanced control schemes have been proposed recently. Generally, the advanced control schemes are complicated and not good for the practical real-time control when they are implemented as control programs. So, in this paper, a relatively simple PI controller is proposed and applied to the position control of mobile robot with the adoption of reference trajectory calculation method used for the AUV(Autonomous Underwater Vehicle) control. The proposed PI controller is programmed using LabVIEW which is popular for its graphical programming characteristics. The simulation and experimental results show the feasibility and effectiveness of the proposed PI controller.