• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.279-282
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• 1996

Collision avoidance is a method to direct a mobile robot without collision when traversing the environment. This kind of navigation is to reach a destination without getting lost. In this paper, we use a genetic algorithm for the path planning and collision avoidance. Genetic algorithm searches for path in the entire, continuous free space and unifies global path planning and local path planning. It is a efficient and effective method when compared with traditional collision avoidance algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.165-173
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• 1995

In order to eliminate position errors existing at the steady state in the motion control of robotic maniprlators, a new fuzzy control algorithm is proposed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller, This controller is applied to the tracking control of robotic manipulators in Cartesian space. Three dimensional look-up table is used to reduce the computational time in rel-time control. Simulation and experimental studies are conducted to evaluate the control performance for the two axis direct drive SCARA robot system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.4-24
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• 2001

Many livings form groups which we consider as collective systems. The collective motion of the group shows various dynamics and patterns, and many model equations are proposed to explain such phenomenon. In our previous work, We proposed simple deterministic model which shows various types of group behaviors. In this paper, we modify it in order to apply to a real robotic system. Here we assume that the space resolution of each robot´s sensors is low and that the sensors detect the nearest robots. It was confirmed the robots with modified model also shows various types of motion.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.255-256
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• 2019

본 논문에서는 물체를 집기(picking) 위해 필요한 깊이 값을 특수카메라인 리얼센스를 사용하여 받아와서 2D 카메라로는 하지 못하는 로봇 팔 피킹 시스템을 구현하였다. 객체 인식은 텐서플로우 객체 검출 라이브러리를 사용하여 정확도를 높였고, ROS 기반의 rviz, moveit, gazebo 등의 패키지를 사용하여 아두이노와 통신하며 로봇팔 하드웨어로 인식된 객체를 피킹하는 시스템을 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.3-146
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• 2001

It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads and open area without any specific mark such as painted guide tine or tape. In this method, Robot navigates with visual sensors, which uses visual information to navigate itself along the road. An Artificial Neural Network System was used to decide where to move. It is designed with USB web camera as visual sensor.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.606-608
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• 1989

Force/torque sensors are now providing widespread practical solutions to manufacturing problems, particularly in the area of automated assembly. The current state of the industry is discussed, including the evolution of transducer and controller design, and the trend of robot manufacturers to integrate force/torque sensors into their robot systems thereby greatly improving cycle time and simplifying the application development task for the end-user. Current and future application areas are discussed as well as the benefits of force/torque sensing.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.518-522
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• 2001

The main problem of the calibration of robots is to measure the position and orientation of a robot end effector. The calibration methods can be used as tool to improve the accuracy of robots without change of the arm or control architecture or robots. But such calibration methods require accurate measurements. Dynamic measurement of position and orientation provides a solution for this problem and improves dynamic accuracy by dynamic calibration of robots. This paper describes the development of the laser tracking system capable of determining the static and dynamic performance of industrial robots. The structure and systems components are presented and basic experimental results are included to demonstrated the instrument performance. The system can be applied to the remote controlled mobile robots as well s the calibration of robots.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.350-356
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• 1997

It is desirable for autonomous robot systems to possess the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Although Q-learning requires a lot of memory and time to optimize a series of actions in a continuous state space, it may not be easy to apply the method to such a real environment. In this paper, for continuous state space applications, to solve problem and a triangular type Q-value model\ulcorner This sounds very ackward. What is it you want to solve about the Q-value model. Our learning method can estimate a current Q-value by its relationship with the neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to move smoothly in a real environment. To show the validity of our method, navigation comparison with Q-learning are given and visual tracking simulation results involving an 2-DOF SCARA robot are also presented.

• Journal of Power Electronics
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• v.8 no.4
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• pp.291-300
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• 2008

In this paper power system and drive-train for omni-directional autonomous mobile robots with multiple energy storage units are presented. Because in proposed system, which is implemented in soccer robots, the ability of power flow control from of multiple separated energy storage units and speed control for each motor are combined, these robots can be derived by more than one power source. This capability, allow robot to diversify its energy source by employing hybrid power sources. In this research Lithium ion polymer batteries have been used for main and auxiliary energy storage units because of their high power and energy densities. And to protect them against deep discharge, over current and short circuit, a protection circuit was designed. The other parts of our robot power system are DC-DC converters and kicker circuit. The simulation and experimental results show proposed scheme and extracted equations are valid and energy management and speed control can be achieved properly using this method. The filed experiments show robot mobility functions to perform the requested motion is enough and it has a high maneuverability in the field.