• 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.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1431-1442
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• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. To be an efficient and precise mobile-task robot, the control uncertainties in the mobile robot should be resolved. Unless the mobile robot provides an accurate and stable base, the task robot cannot perform various tasks. For the control of the mobile robot, an absolute position sensor is necessary. However, on account of rolling and slippage of wheels on the ground, there does not exist any reliable position sensor for the mobile robot. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. For this calibration, a camera is attached on the top of the task robot to capture the images of the objects. These images are used to estimate the pose of the camera itself with respect to the known objects. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and propagated to get the pose of a mobile robot. Two types of objects are used here as samples of work-pieces: a polygonal and a cylindrical object. With these two samples, the proposed active calibration scheme is verified experimentally.

• Journal of Mechanical Science and Technology
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• v.14 no.6
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• pp.605-621
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• 2000

A mobile manipulator-a serial connection of a mobile platform and a task robot-is redundant by itself. Using its redundant freedom, a mobile manipulator can move in various modes, i. e., can perform dexterous tasks. In this paper, to improve task execution efficiency utilizing redundancy, optimal configurations of the mobile manipulator are maintained while it is moving to a new task point. Assuming that a task robot can perform the new task by itself, a desired configuration for the task robot can be pre-determined. Therefore, a cost function for optimality can be defined as a combination of the square errors of the desired and actual configurations of the mobile platform and of the task robot. In the combination of the two square errors, a newly defined mobility of a mobile platform is utilized as a weighting index. With the aid of the gradient method, the cost function is minimized, so the tasle that the mobile manipulator performs is optimized. The proposed algorithm is experimentally verified and discussed with a mobile manipulator, PURL-II.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.1-7
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• 1996

This paper addresses the control problem of a mobile robot supporting a task robot with needs to be positioned precisely. The main difficulty residing in the precise control of a mobile robot supporting a task robot is providing an accurate and stable base for the task robot. That is, the end-plate of the mobile robot which is the base of the task robot can not be positioned accurately without external position sensors. This difficulty is resolved in this paper through the vision information obtained from the camera attached at the end of a task robot. First of all, the camera parameters were measured by using the images of a fixed object captured by the camera. The measured parameters include the rotation, the position, the scale factor, and the focal length of the camera. These parameters could be measured by using the features of each vertex point for a hexagonal object and by using the pin-hole model of a camera. Using the measured pose(position and orientation) of the camera and the given kinematics of the task robot, we calculate a pose of the end-plate of the mobile robot, which is used for the precise control of the mobile robot. Experimental results for the pose estimations are shown.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.734-739
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• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. For the control of the mobile robot, an absolute position sensor is necessary. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and that is propagated to getting the pose of a mobile robot. With the experiments in the corridor, the proposed active calibration scheme is verified experimentally.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.166-169
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• 2004

In this paper show how to design a redundant robot which is suitable for the multiple task without any constraints on the workspace. The implementation is possible by the rigid connection of a mobile robot and a task robot. Use a five joint articulated robot as the task robot; designed the 3 joint mobile robot for this usage. For a task execution assigned to the redundant robot, not only the task robot but the mobile robot should work in the coordinated way. therefore, a kinematic connection of the two robots should be cleary represented in a frame. And, also the dynamic interaction between the two robots needs to be analyzed. Clarified these issues considering the control of the redundant robot. Finally, demonstrate away of utilization of the redundancy as the cooperation between the mobile robot and the task robot to execute a common task.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.401-401
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• 2000

A mobile manipulator-a serial connection of a mobile robot and a task robot is redundant by itself. Using its redundant freedom, a mobile manipulator can move in various modes, and perform dexterous tasks. An interesting question,

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.206-212
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• 2009

This paper presents an optimized integrated task planning and control approach for manipulating a nonholonomic robot by mobile manipulators. Then, we derive a kinematics model and a mobility of the mobile manipulator(M2) platform considering it as the combined system of the manipulator and the mobile robot. to improve task execution efficiency utilizing the redundancy, optimal trajectory of the mobile manipulator(M2) platform are maintained while it is moving to a new task point. A cost function for optimality can be defined as a combination of the square errors of the desired and actual configurations of the mobile robot and of the task robot. In the combination of the two square errors, a newly defined mobility of a mobile robot is utilized as a weighting index. With the aid of the gradient method, the cost function is minimized, so the path trajectory that the M2 platform generates is optimized. The simulation results of the 2 ink planar nonholonomic M2 platform are given to show the effectiveness of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.153-160
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• 2008

One of the most important features of the Mobile Manipulator is redundant freedom. Using it's redundant freedom, a Mobile Manipulator can move in various modes, and perform dexterous motions. In this paper, to improve robot job performance, two robots -mobile robot, task robot- are joined together to perform a job, we studied the optimal position and posture of a Mobile Manipulator to achieve a minimum of movement of each robot joint. Kinematics of mobile robot and task robot is solved. Using the mobility of a Mobile robot, the weight vector of robots is determined. Using the Gradient method, global motion trajectory is minimized, so the job which the Mobile Manipulator performs is optimized. The proposed algorithm is verified with PURL-II which is Mobile Manipulator combined Mobile robot and task robot, and the results are discussed.

• Journal of information and communication convergence engineering
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• v.3 no.1
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• pp.33-37
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• 2005

One of the most important feature of the Mobile Manipulator is redundant freedom. Using the redundant freedom, Mobile Manipulator can move various mode, perform dexterous motion. In this paper, to improve robot job ability, as two robots perform a job in co-operation control, we studied optimal position and posture of Mobile Manipulator with minimum movement of each robot joint. Kinematics of mobile robot and task robot is solved. Using mobility of Mobile robot, weight vector of robots is determined. Using Gradient methode, global motion trajectory is minimized. so the job which Mobile Manipulator perform is optimized. The proposed algorithm is verified with PURL-II which is Mobile Manipulator combined Mobile robot and task robot. and discussed the result.