• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.501-507
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• 2013

This paper presents the development and balancing control of GYROBO, a one wheeled mobile robot system. GYROBO is a disc type one wheel mobile robot that has three actuators, a drive motor, a spin motor, and a tilt motor. The dynamics and kinematics of GYROBO are analyzed, and simulation studies conducted. A one-wheeled robot, GYROBO is built and its balancing control is performed. Experimental studies of GYROBO's balancing abilities are conducted to demonstrate the gyroscopic effects generated by the spin and tilt angles of a flywheel.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.127-132
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• 1998

Mobile wheeled robots are nonholonomically constrained systems. Generally, it is very difficult to describe the motion of mechanical systems with nonintegrable nonholonomic constraints. An objective of this study is to describe the motion of a robot with a free wheel. The motion of holonomically and/or nonholonomically constrained system can be simply determined by Generalized Inverse Method presented by Udwadia and Kalaba in 1992. Using the method, we describe the exact motion of the robot and determine the constraint force exerted on the robot for satisfying constraints imposed on it. The application illustrates the ease with which the Generalized Inverse Method can be utilized for the purpose of control of nonlinear system without depending on any linearization, maintaining precision tracking motion and explicit determination of control forces of nonholonomically constrained system.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.95-101
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• 2020

In situations where mobile robots are operated either by autonomous systems or human operators, such as smart factories, priority-based teleoperation is crucial for the multiple operators with different priority to take over the right of the robot control without conflict. This paper proposes a priority-based teleoperation system for multiple operators to control the robots. This paper also introduces an efficient joystick-based robot control command generation algorithm for differential-drive mobile robots. The proposed system is implemented with ROS (Robot Operating System) and embedded control boards, and is applied to Pioneer 3AT mobile robot platform. The experimental results demonstrate the effectiveness of the proposed joystick control command algorithm and the priority-based control input selection.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.259-262
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• 1997

This paper presents a visual servoing of RV-M2 robot manipulators to track and grasp moving object, using pruned dynamic recurrent neural networks(DRNN). The object is stationary in the robot work space and the robot is tracking and grasping the object by using CCD camera mounted on the end-effector. In order to optimize the structure of DRNN, we decide the node whether delete or add, by mutation probability, first in case of delete node, the node which have minimum sum of input weight is actually deleted, and then in case of add node, the weight is connected according to the number of case which added node can reach the other nodes. Using evolutionary programming(EP) that search the struture and weight of the DRNN, and evolution strategies(ES) which train the weight of neuron, we pruned the net structure of DRNN. We applied the DRNN to the Visual Servoing of a robot manipulators to control position and orientation of end-effector, and the validity and effectiveness of the pro osed control scheme will be verified by computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.651-656
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• 2014

This paper presents a compensation method for an accelerometer to measure acceleration data accurately when a robot manipulator moves slowly. Although the accelerometer works fine under the fast movement of a robot manipulator, low cost accelerometers provide relatively inaccurate acceleration data under slow movements. In order to correct the error of the sensor data in the slow motion, correction factors are obtained experimentally. Then those corrected data are used for the disturbance observer. Experimental studies of the position control of a robot manipulator are conducted by applying the DOB (Disturbance Observer) control using corrected acceleration data.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.607-612
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• 2008

This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.1-14
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• 2005

This paper presents an obstacle detection algorithm based on the consecutive and the cooperative range sensor scanning schemes. For a known environment, a mobile robot scans the surroundings using a range sensor that can rotate 3600°. The environment is rebuilt using nodes of two adjacent walls. The robot configuration is then estimated and an obstacle is detected by comparing characteristic points of the sensor readings. In order to extract edges from noisy and inaccurate sensor readings, a filtering algorithm is developed. For multiple robot localization, a cooperative scanning method with sensor range limit is developed. Both are verified with simulation and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.50-57
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• 1995

In this paper, the design and the implementation of the controller for an articulate robot, which is developed in our Automatic Control Laboratory, are mainly discussed. The controller reduces software computational load via distributed processing method using multiple CPU's, and simplifies structures by the time-division control with TMS320C31 DSP chip. The method of control is based on the fuzzy-compensated PID control with scale factor, which compensates for the influence of load variation resulting from the various postures of the robot with conventional PID scheme. The application of the proposed controller to the robot system with DC servo-motors shows some excellent control capabilities. Also, the response characteristics of system for the various trajectory commands verify the superiority of the controller.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.40-45
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• 2016

This paper presents the neuro-fuzzy control method for balancing a two-wheel mobile robot. A two-wheel mobile robot is built for the experimental studies. On-line learning algorithm based on the back-propagation(BP) method is derived for the Takagi-Sugeno(T-S) neuro-fuzzy controller. The modified error is proposed to learn the B-P algorithm for the balancing control of a two-wheel mobile robot. The T-S controller is implemented on a DSP chip. Experimental studies of the balancing control performance are conducted. Balancing control performances with disturbance are also conducted and results are evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.470-476
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• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.