• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4482-4488
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• 2014

This paper proposes the creation scheme of a threat map for robot global path planning. The threat map was generated using neural network theory by analyzing the robot's armament state and the menace information of an enemy or obstacle. In addition, the performance of the suggested method was verified using the compared result of the damage amount and existing robot path data.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.444-452
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• 2005

A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.66-73
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• 2016

An Inertial Measurement Unit (IMU)-based Attitude and Heading Reference System (AHRS) can calculate attitude and heading information with long-term accuracy and stability by combining gyro, accelerometer, and magnetic compass signals. Motivated by this characteristic of the AHRS, this paper presents a Motion-Tracking and Localization (MTL) method for a person or walking robot using multi-AHRSs. Five AHRSs are attached to the two calves, two thighs, and waist of a person/walking robot. Joints, links, and coordinate frames are defined on the body. The outputs of the AHRSs are integrated with link data. In addition, a supporting foot is distinguished from a moving foot. With this information, the locations of the joints on the local coordinate frame are calculated. The experimental results show that the presented MTL method can track the motion of and localize a person/walking robot with long-term accuracy in an infra-less environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.314-320
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• 2006

Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2806-2808
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• 2005

The Controller Area Network (CAN) is being widely used for real-time control application and small-scale distributed computer controller systems. When the stuff bits are generated by bit-stuffing mechanism in the CAN network, it causes jitter including variations in response time and delay. In order to eliminate this jitter, stuff bit must be controlled to minimize the response time and reduce the variation of data transmission time. At first, this paper shows that conventional CAN protocol causes the transmission time delay. Secondly, this paper proposes the method to reduce the stuff bits by restriction of available identifier. Finally, data manipulation method can be reduced the number of stuff-bits in the data field. The proposed restriction method of ID and manipulating data field are pretty useful to the real-time control strategy with respect to performance. These procedures are implemented in local controllers of the ISHURO (Inha Semyung Humanoid Robot).

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1832-1835
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• 1997

Off-line programming systems are widely spread in assembly lines of minute electronic products to huge offshore structures. Any OLP system has to be calibrated before the on-line robot tasks are performed because there are inherent differences between the CAD model on OLP and the real robot workspace. This paper uses simple geometric expressions to propose a calibration method applicable to an OLP for SCARA robots. A positioning task on the two-dimensional horizontal surface was used in the error analysis of a SCARA robot and the anaysis shows that the inaccuracy results from the two error sources non-zero offset angles of two rotational joints at the zero return and differences in link lengths. Pen marks on a sheet of plotting paper are used to determine the accurate data on the joint centers and link dimensions. The calculated offset angles and link lengths are fed back to the OLP for the calibration of the CAD model of the robot and task environments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1087-1090
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• 2004

stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. In this paper we persent a visual approach to the problem of object grasping. First we propose object recognization method which can find the object position and pose using feature points. A robot recognizes the feature point to Object. So a number of feature point is the more, the better, but if it is overly many, the robot have to process many data, it makes real-time image processing ability weakly. In other to avoid this problem, the robot selects only two point and recognize the object by line made by two points. Second we propose trajectory planing of the robot manipulator. Using grometry of between object and gripper, robot can find a goal point to translate the robot manipulator, and then it can grip the object successfully.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2350-2355
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• 2005

In this paper, we introduce biped walking robot which can static walking with 22 degree-of-freedoms. The developed biped walking robot is 480mm tall and 2500g, and 22 RC servo motors are used to actuate. Before made an active algorithm, we generated the motions of robot with the motion simulator which developed using by C language. The two dimension simulator is Based on the inverse kinematics and D-H transform. The simulator implements various motions as inputted the ankle's trajectory. Also we developed a simulator which is applied the principle of inverted pendulum to acquires the center of gravity. As we use this simulator, we can get the best appropriate angle of ankle and pelvis when the robot lifts up its one side leg during the working. We implement the walking motions which is based on the data(angle) getting from both of simulators. The robot can be controlled by text shaped command through RF signal of wireless modem which connected with laptop computer by serial cable.