• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.71-79
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• 1997

This paper introduces a methodology of the precise control of a mobile/task robot using visual information captured bythe camera attached at the hand of the task robot. The major problem residing in the precise control of mobile/task robot is providing an accurate and stable base for the task robot through the precise control of mobile robot. On account of uncertainties on the surface, the precise control of mobile robot is not feasible without using external position sensor. In this paper, the methodology for the precise control of mobile robot is proposed, which recognizes the position of mobile robot using the camera attached at the hand of the task robot. While the task robot is approaching to an assembly part, the position of mobile robot is measured using the line correspondence between the image capturesd by the camera and the real assembly part, and using the kinematic transformation from the hand of the task robot to the mobile robot. To verify the solidness of this method, experimental data for the measurement of camera position/orientation and for the precise control of mobile robot using measurement are shown.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.460-463
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• 1995

The present paper studies a robot manipulator's contact tasks on the uncertain flexible objects. The flexible object's distributed parameter model is approximated into a lumped "position state-varying" model. By using the well-known nonlinear feedback compensation, the robot's control space is decomposed into the position control subspace and the object's torque control subspace. The optimal state feedback is designed for the position loop, and the robot's contact force is controlled through controlling the resultant torque on the object using model-reference simple adaptive control. Experiments of a PUMA robot interacting with an aluminum plate show the effectiveness of this control approach. approach.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.15-25
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• 2010

The objective of this study is to investigate the optimal arrangement of cameras used for the robot's vision control scheme. The used robot's vision control scheme involves two estimation models, which are the parameter estimation and robot's joint angle estimation models. In order to perform this study, robot's working region is divided into three work spaces such as left, central and right spaces. Also, cameras are positioned on circular arcs with radius of 1.5m, 2.0m and 2.5m. Seven cameras are placed on each circular arc. For the experiment, nine cases of camera arrangement are selected in each robot's work space, and each case uses three cameras. Six parameters are estimated for each camera using the developed parameter estimation model in order to show the suitability of the vision system model in nine cases of each robot's work space. Finally, the robot's joint angles are estimated using the joint angle estimation model according to the arrangement of cameras for robot's point-position control. Thus, the effect of camera arrangement used for the robot's vision control scheme is shown for robot's point-position control experimentally.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.772-776
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• 1997

For a robot to perfom more versatile tasks, it is invitable for the robot's end-effector to come into contact with its environment. In thos case, to achieve better performance, it is necessary to properly control the contact force between the robot and the environment. In thos work, hybrid control theory is studied and is verified through experiment using a 3 DOF robot. In the experiment, two position/force controllers are used. Fist, proportional-integral-derivative controller is used as the controller for both position and force. Second, computed-torque method is used as the position controller, and proportional-integral-derivative controller is used as the force controller. For a proper modeling used in computed-torque method, the friction torque is measured by experiment, and compensation method is studied. The hybrid control method used in this experiment effectively control the contact force between the end-effector and the environment for various types of jobs.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.555-555
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• 2000

This study is concentrated on the development of hight speed multi-object image processing algorithm, and based on these a1gorithm, vision control scheme is developed for the robot's position control in real time. Recently, the use of vision system is rapidly increasing in robot's position centre. To apply vision system in robot's position control, it is necessary to transform the physical coordinate of object into the image information acquired by CCD camera, which is called image processing. Thus, to control the robot's point position in real time, we have to know the center point of object in image plane. Particularly, in case of rigid body, the center points of multi-object must be calculated in a image plane at the same time. To solve these problems, the algorithm of multi-object for rigid body control is developed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.577-582
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• 2015

This paper proposes an efficient detection of absolute position of a robot joint using two incremental encoders. We considers a robot joint comprising a motor, a reducer, two encoders, and a motor drive. An incremental(first) encoder provides motor's rotor position or input position of reducer while another incremental(second) encoder does output position of the reducer. A table is made where the relationship between the first and the second encoder counts is recorded. The key point is placed where the table is constructed: when a pulse occurs in the second encoder, there exists a corresponding unique count value of the first encoder. The absolute position is detected using the table by searching the second encoder position corresponding to the first encoder count value when a pulse occurs in the second encoder. The proposed method needs a small rotation, as just one second encoder's pulse angle, for the initial absolute position detection.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.249-254
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• 2015

Buoys are widely used in marine areas because they can mark positions and simultaneously acquire and exchange underwater, surface, and airborne information. Recently, the need for controlling and optimizing a buoy's position and attitude has been raised to achieve successful communication in a heterogeneous collaborative network composed of an underwater robot, a surface robot, and an airborne robot. A buoy in the form of a marine robot would be ideal to address this issue, as it can serve as a moving node of the communication network. Therefore, a buoy-based autonomous surface robot-kit with the abilities of sonar-based avoidance, dynamic position control, and static attitude control was developed and is discussed in this paper. The test and evaluation results of this kit show the possibility of real-world applications and the need for additional studies.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.