• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1925-1936
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• 2010

In this paper, multi-legged robot was designed and produced using stable walking pattern algorithm. The robot had embedded camera and wireless communication function and it is possible to recognize both hand posture and obstacles. The algorithm decided moving paths, and recognized and avoided obstacles through Hough Transform using Edge Detection of inputed image from image sensor. The robot can be controlled by hand posture using Mahalanobis Distance and average value of skin's color pixel, which is previously learned in order to decide the destination. The developed system has shown obstacle detection rate of 96% and hand posture recognition rate of 94%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.418-421
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• 2004

This research is that analysis multi-body system that have flexibility. We composed system consisted of crane, part of traveling and robot. And we analyzed the aspect of vibration when this system runs using ADAMS. Through this research we can analyze vibration and displacement of end-effect part of the large size robot. And this research can became reference that is going to analyze resemblant dynamic system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.691-694
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• 2000

In this paper, a motion control algorithm is proposed by using neural network system, which makes a robot arm successfully avoid unexpected obstacle when the robot is moving from the start to the goal position. During the motion, if there is an obstacle the vision system recognizes it. And in every time the optimization-algorithm quickly chooses a motion among the possible motions of robot. The proposed algorithm has a good avoidance characteristic in simulation.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.739-744
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• 2008

Human-like biped robot is a representative multi-links manipulator and undoubted redundancy system. However many researchers separate biped robot into each limb and analyze the members individually for the convenience analysis. This approach is not desirable for natural trajectory generation and energy optimization. This paper proposes the analysis method considering both legs together and the weighted pseudoinverse optimizing energy consumption.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.253-260
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• 2015

There are many efforts to mechanize the process for underwater port construction due to the severe and adverse working environment. This paper presents an underwater construction robot to level rubbles on the seabed for port construction. The robot is composed of a blade and a multi-functional arm to flatten the rubble mound with respect to the reference level at uneven terrain and to dig and dump the rubbles. This research analyzes the kinematics of the blade and the multi-functional arm including track and swing motions with respect to a world coordinate assigned to a reference depth sensor. This analysis is conducted interfacing with the position and orientation sensors installed at the robot. A hydraulic control system is developed to control a track, a blade and a multi-functional arm for rubble leveling work. The experimental results of rubble leveling work conducted by the robot are presented in land and subsea. The working speed of the robot is eight times faster than that of a human diver, and the working quality is acceptable. The robot is expected to have much higher efficiency in deep water where a human diver is unable to work.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.159-164
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• 2011

In this study, a crab robot is implemented in H/W based on four-bar linkage mechanism and Jansen mechanism, and its kinematics is analysed. A vision camera is attached to the mechanism, which makes the proposed robot a kind of biologically inspired robot for image acquisition. Three ultrasonic sensors are adopted for obstacle avoidance. In addition, the biologically inspired robot can achieve the mission appointed by a programmer outside, based on RF and Blue-tooth communication module. For the design and implementation of a crab robot, it is need to get joint variable, a foot point, and their relation. Thus, the proposed kinematic analysis is very important process for the design and implementation of legged robots.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.847-848
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• 2013

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.944-947
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• 1996

Realization of autonomous agents that organize their own internal structure in order to behave adequately with respect to their goals and the world is the ultimate goal of AI and Robotics. Reinforcement learning gas recently been receiving increased attention as a method for robot learning with little or no a priori knowledge and higher capability of reactive and adaptive behaviors. In this paper, we present a method of reinforcement learning by which a multi robots learn to move to goal. The results of computer simulations are given.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1840-1843
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• 1997

The task environment of a robot is changing rapidly and task itself becomes complicated due to current industrial trends of multi-product and small lot size production. A convenient user-interfaced off-line programming(OLP) system is being developed in order to overcome the difficulty in teaching a robot task. Using the OLP system, operators can easily teach robot tasks off-line and verify feasibility of the task through simulation of a robot prior to the on-line execution. However, some task errors are inevitable by kinematic differences between the robot model in OLP and the actual robot. Three calibration methods using image information are proposed to compensate the kinematic differences. These methods compose of a relative position vector method, three point compensation method, and base line compensation method. To compensate a kinematic differences the vision system with one monochrome camera is used in the calibration experiment.