• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.19-24
• /
• 1992

Real-time mobile robot controllers usually have been designed with an emphasis on control theory ignoring the importance of system integration. This paper demonstrates that useful mobile robots require a real time controller with a wide range of capabilities in addition to control theory. These capabilities include: path-planning, position estimation, path tracking control and wheel control. An architectural framework supporting these capabilities has been designed and implemented. Using this frame work, individual modules such as a path planner, a path tracking controller, position estimators, wheel controllers and other cruical elements have been successfully integrated into the control system for the LCAR robot which was developed as a proto-type mobile robot in our laboratory. The context of the research, the architecture, its implementation and performance results from experiments are discussed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.125-130
• /
• 1999

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.7
• /
• pp.155-162
• /
• 2003

We propose a new technique far real-tine controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Caussian function as a unit function in the fuzzy neural network. and a 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-foray. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2311-2318
• /
• 2005

Progress in the LCD industries has been very rapid. Therefore, their manufacturing lines require larger LCD glass-handling robots and more precise path control of the robots. In this paper, we present two practical advanced algorithms for high-precision path generation of an LCD glass-handling robot. One is high-precision path interpolation for continuous motion, which connects several single motions and is a reliable solution for a short robot cycle time. We demonstrate that the proposed algorithm can reduce path error by approximately 91% compared with existing algorithms without increasing cycle time. The second is real-time static deflection compensation, which can optimally compensate the static deflection of the handling robot without any additional sensors, measurement instruments or mechanical axes. This reduces vertical path error to approximately 60% of the existing system error. All of these algorithms have been commercialized and applied to a seventh-generation LCD glass-handling robot.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.12 no.1
• /
• pp.35-42
• /
• 2013

This paper proposes a new approach to the designed of visual feedback control system based on visual servoing method. The main focus of this paper is presented how it is effective to use many features for improving the accuracy of the visual feedback control of industrial articulated robot for assembling and inspection of parts. Some rank conditions, which relate the image Jacobian, and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. The effectiveness of redundant features is verified by the real time experiments on a SCARA type robot(FARA) made in samsung electronics company.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.154-161
• /
• 1999

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1996.03a
• /
• pp.79-84
• /
• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.5 no.4
• /
• pp.26-37
• /
• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.10
• /
• pp.998-1004
• /
• 2008

In this paper, a visual servoing control technique of humanoid robot arms is implemented for tracking a moving object. An embedded time-delayed controller is designed on an FPGA(Programmable field gate array) chip and implemented to control humanoid robot arms. The position of the moving object is detected by a stereo vision camera and converted to joint commands through the inverse kinematics. Then the robot arm performs visual servoing control to track a moving object in real time fashion. Experimental studies are conducted and results demonstrate the feasibility of the visual feedback control method for a moving object tracking task by the humanoid robot arms called the ROBOKER.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.253-257
• /
• 2004

Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.