• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2417-2419
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• 2001

A path planning is one of the main subjects in a mobile robot. It is divided into two parts. One is a global path planning and another is a local path planning. This paper, using the formal two methods, presents that the mobile robot moves to multi-targets with avoiding unknown obstacles. For the shortest time and the lowest cost, the mobile robot has to find a optimal path between targets. To find a optimal global path, we used GA(Genetic Algorithm) that has advantage of optimization. After finding the global path, the mobile robot has to move toward targets without a collision. FLC(Fuzzy Logic Controller) is used for local path planning. FLC decides where and how faster the mobile robot moves. The validity of the study that searches the shortest global path using GA in multi targets and moves to targets without a collision using FLC, is verified by simulations.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.55-61
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• 2020

Getting on and off an elevator is one of the most important parts for multi-floor navigation of a mobile robot. In this study, we proposed the method for the pose recognition of elevator doors, safe path planning, and motion estimation of a robot using RGB-D sensors in order to safely get on and off the elevator. The accurate pose of the elevator doors is recognized using a particle filter algorithm. After the elevator door is open, the robot builds an occupancy grid map including the internal environments of the elevator to generate a safe path. The safe path prevents collision with obstacles in the elevator. While the robot gets on and off the elevator, the robot uses the optical flow algorithm of the floor image to detect the state that the robot cannot move due to an elevator door sill. The experimental results in various experiments show that the proposed method enables the robot to get on and off the elevator safely.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.164-173
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• 1999

Robot calibration needs accurate measurements of robot end-effector position at a number of different robot configurations. One of the efficient ways of the measurement is "Touching on Jig" method suggested in [7], which utilizes a touch sensor and a fixture consisting of various sizes of blocks. By moving the end-effector to touch the surface of a block whose position relative to the other is known, the end-effector position relative to the fixture coordinate system can be obtained at the instant of touching. However, the global size of fixture is too small to cover the various configurations of the robot. Because of the manufacturing difficulties, the fixture cannot be manufactured large enough for well distributed position measurement. It results in the improvement of robot accuracy only in the limited space near to the fixture rather than over the whole space of the robot working volume. The paper proposes a method to resolve the above problem by measuring the end-effector positions with respect to several different coordinate system using the same measurement devices. It is found that the proposed method leads the improvements of robot position accuracy over the large space of working volume. The experimental studies are performed to show the validity of the method and their results are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.162-167
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• 1991

The manipulability ellipsoid and the force ellipsoid for a single robot are extended to the case of a multi-robot system. The force ellipsoid is applied to solve the optimal load distribution for the multi-robot system. Two cases are considered in solving the optimal load distribution. In one case, there are no constraints on the joint torques, and the analytic solution ;a given. In the other case, the torque constraints are given in terms of the maximum power consumption, and the algorithm for the solution is proposed.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.765-766
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• 2006

The ecology of Physically Embedded Intelligent Systems (PEIS) is a new multi robotic framework conceived by integrating insights from the fields of autonomous robotics and ambient intelligence. A PEIS-Ecology is a network of intelligent robotic devices that can provide the user with assistance, information, communication, and entertainment services. In this paper we introduce the concept of PEIS Ecology, and illustrate a concrete realization of a PEIS-Ecology.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.308-313
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• 2018

In this paper, we propose a sampled-data model predictive tracking control deign for leader-following control of multi-mobile robot system. The error dynamics of leader-following robots is modeled as a Linear Parameter Varying (LPV) model. Also, the Lyapunov function is presented to guarantee stability of the networked control system. Based on the stabilization condition using a quadratic Lyapunov function approach, model predictive sampled-data controller is designed. Finally, the leader-following control of multi mobile robots is simulated to show effectiveness of the proposed method.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.210-217
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• 2009

This paper introduces a design of multi-dimensional complex emotional model for various complex emotional expression. It is a novel approach to design an emotional model by comparison with conventional emotional model which used a three-dimensional emotional space with some problems; the discontinuity of emotions, the simple emotional expression, and the necessity of re-designing the emotional model for each robot. To solve these problems, we have designed an emotional model. It uses a multi-dimensional emotional space for the continuity of emotion. A linear model design is used for reusability of the emotional model. It has the personality for various emotional results although it gets same inputs. To demonstrate the effectiveness of our model, we have tested with a human friendly robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.45-46
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.765-766
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.295-296
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• 2013