• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.551-556
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• 2014

This paper proposes a balancing control and driving control of a bicycle robot based on dynamic modeling of the bicycle robot, which has been derived using the Lagrange equations. For the balancing control of the bicycle robot, a reaction wheel pendulum method has been adopted in this research. By using the dynamics equations of the bicycle robot, an LQR controller has been designed for a balancing and driving control of a bicycle robot. The performance of the balance control is verified experimentally before the driving control, which shows a stable posture within one degree vibrations. To show the dynamic characteristics of the bicycle robot during driving, a trapezoidal velocity trajectory is selected as the references. Through simulations and real experiments, the effectiveness of the proposed algorithm has been demonstrated.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.4
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• pp.217-226
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• 2014

Since the world has changed to a society of 21st century high-tech industries, the modern people have become reluctant to work in a difficult and dirty environment. Therefore, unmanned technologies through robots are being demanded. Now days, effects such as voice, control, obstacle avoidance are being suggested, and especially, voice recognition technique that enables convenient interaction between human and machines is very important. In this study, in order to conduct study on the stable motion control of the robot system that has mobile-manipulator structure and is voice command-based, kinetic interpretation and dynamic modeling of two-armed manipulator and three-wheel mobile robot were conducted. In addition, autonomous driving of three-wheel mobile robot and motion control system of two-armed manipulator were designed, and combined robot control through voice command was conducted. For the performance experiment method, driving control and simulation mock experiment of manipulator that has two-armed structure was conducted, and for experiment of combined robot motion control which is voice command-based, through driving control, motion control of two-armed manipulator, and combined control based on voice command, experiment on stable motion control of voice command-based robot system that has mobile-manipulator structure was verified.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.277-285
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• 2020

A differential drive wheeled robot is a kind of mobile robot suitable for indoor navigation. Model predictive control is an optimal control technique with various advantages and can achieve excellent performance. One of the main advantages of model predictive control is that it can easily handle constraints. Therefore, it deals with realistic constraints of the mobile robot and achieves admirable performance for trajectory tracking. In addition, the intention of the robot can be properly realized by adjusting the weight of the cost function component. This control technique is applied to the local planner of the navigation component so that the mobile robot can operate in real environment. Using the Robot Operating System (ROS), which has transcendent advantages in robot development, we have ensured that the algorithm works in the simulation and real experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.229-232
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• 1996

The position control accuracy of the robot arm is decreased significantly when a long arm robot is operated at high speed. In this case, the robot arm must be modeled as a flexible structure, not a rigid one, and its control system will be necessarily designed with its elastic modes taken into account. In this paper, the vibration control of a one-link flexible robot arm is presented. The robot system consists of a flexible arm manufactured with thin aluminium plate, AC servomotor with a harmonic drive for speed reduction, optical encoder and accelerometer. The system is modeled with limited number of elastic modes, and its parameters are determined from the results of the experiments. The implemented control schemes are LQ control and sliding mode control. The experiments and digital simulations are carried out to test the validity of the system modeling, controller design, and active control implementation.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.319-328
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• 2010

This paper proposes a robust adaptive fuzzy tracking control scheme for a nonholonomic mobile robot with external disturbances as well as parameter uncertainties in the robot kinematics, the robot dynamics, and the actuator dynamics. In modeling a mobile robot, the actuator dynamics is integrated with the robot kinematics and dynamics so that the actuator input voltages are the control inputs. The presented controller is designed based on a FBFN (Fuzzy Basis Function Network) to approximate an unknown nonlinear dynamic function with the uncertainties, and a robust adaptive input to overcome the uncertainties. When the controller is designed, the different parameters for two actuator models in the actuator dynamics are taken into account. The proposed control scheme does not require the kinematic and dynamic parameters of the robot and actuators accurately. It can also alleviate the input chattering and overcome the unknown friction force. The stability of the closed-loop control system including the kinematic control system is guaranteed by using the Lyapunov stability theory and the presented adaptive laws. The validity and robustness of the proposed control scheme are shown through a computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2342-2345
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• 2005

Robot control system considers various requirements. Firstly, it needs adaptation for unpredictable and dynamic environment. Secondly, it needs way to make do not injurious action to human because live with a person. Thirdly, it needs processing about aim of robots. In this paper proposed that these requirements effective robot control architecture. Robot control architecture can divide Deliberative, Reactive, Hybrid. Recently, robot control architecture that come Deliberative and use hybrid architecture that apply advantage of Reactive architecture is studied much. Hybrid control purpose to combine the real-time response of Reactive with the rationality of Deliberative. Our purpose is enhancement of hybrid architecture that is studied in these days. Proposed architecture that applied human's nervous system can reduce relativity between each module of existent architecture and drive response speed guarantee and safe robot action.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.37-40
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• 2002

Intelligent Wearable Module is intelligent system that arises when a human is part of the feedback loop of a computational process like a certain control system. Applied system is mobile robot. This paper represents the mobile robot control system remote controlled by Intelligent Wearable Module. So far, owing to the development of internet technologies, lots of remote control methods through internet have been proposed. To control a mobile robot through internet and guide it under unknown environment, We propose a control method activated by Intelligent Wearable Module. In a proposed system, PDA acts as a user interface to communicate with notebook as a controller of the mobile robot system using TCP/IP protocol, and the notebook controls the mobile robot system. Tlle information about the direction and velocity of the mobile robot feedbacks to the PDA and the PDA send new control method produced from the fuzzy inference engine.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.77-84
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• 2006

This paper describes the design and implementation of a robot's gripper control system. In order to safely grasp an unknown object using the robot's gripper, the gripper should detect the force of gripping direction and the force of gravity direction, and should perform the force control using the detected forces and the robot's gripper control system. In this paper, the robot's gripper control system is designed and manufactured using DSP(Digital Signal Processor), and the gripper is composed of two 6-axis force/moment sensors which measures the Fx force(force of x-direction), Fy force, Fz force, and the Mx moment(moment of x-direction), My moment, Mz moment at the same time. The response characteristic test of the system is performed to determine the proportional gain Kp and the integral gain Ki of PI controller. As a result, it is shown that the developed robot's gripper control system grasps an unknown object safely.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.339-342
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• 1996

In this paper, the method for controlling PUMA robot using F/T sensor is described. In the part of the setup automation, robot is used. The F/T sensor is located at robot end-effector and various experiments are executed such as peg in hole, gripping objects, tool changing, etc.