• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.25.1-25
• /
• 2001

Intelligent Space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. Thus, it is desirable for a mobile robot to carry out human-affnitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow walking human as stably and precisely as possible.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.2
• /
• pp.7-16
• /
• 2002

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.50.2-50
• /
• 2002

1. Introduction 2. Reduced-Order Model of Robot System 3. Model-Based Control 4. Simulation Results 5. Experimental Results and Considerations 6. Conclusions

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.34.2-34
• /
• 2002

● Introduction ● The environment of the RoboSot ● Extracting landmarks & feature points ● Experimental results ● Conclusion

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.2
• /
• pp.96-101
• /
• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.360-365
• /
• 2003

In this paper, we have developed a general purpose motion controller using an FPGA(Field Programmable Gate Array). The multi-PID controllers on a single chip are implemented as a system-on-chip for multi-axis motion control. We also develop a PC GUI for an efficient interface control. Comparing with the commercial motion controller LM 629 it has multi-independent PID controllers so that it has several advantages such as space effectiveness, low cost and lower power consumption. In order to test the performance of the proposed controller, robot finger is controlled. The robot finger has three fingers with 2 joints each. Finger movements show that position tracking was very effective. Another experiment of balancing an inverted pendulum on a cart has been conducted to show the generality of the proposed FPGA PID controller. The controller has well maintained the balance of the pendulum.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.8-17
• /
• 1998

Autonomous mobile robot agents(AMRAs) are robots which perform a given task by the same distributed self-organizing rules. In this paper, we let them form an equi-distance circle for the task of cooperative behaviors. Here, we suggest an algorithm to perform the taqk and then utilize a fuzzy system to improve the algorithm. It is shown that various cooperative activities appear in the simulation and particularly chaotic behaviors also appear by increasing the robot speed. Moreover, we prove the characteristics of this chaotic behaviors by calculating Lyapunov exponent.

• Journal of Welding and Joining
• /
• v.27 no.2
• /
• pp.57-62
• /
• 2009

This research was carried out to improve the productivity in the subassembly process of shipbuilding through optimal work planning for the shortest work time. The work time consist of welding time, moving time of gantry, teaching time of robot and robot motion time. The shortest work time is accomplished by even distribution of work and the shortest welding sequence. Even distribution of work was done by appling the simple algorithm. The shortest work sequence was determined by using GA. The optimal work planning decreased the total work time of the subassembly process by 4.1%. The result showed the effectiveness of the suggested simple algorithm for even distribution of work and GA for the shortest welding sequence.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.2
• /
• pp.124-132
• /
• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

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