• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.121-127
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• 2019

This paper proposes an operator-centric velocity generation and control algorithm for differential-drive mobile robots, which are widely used in many industrial applications. Most of the previous works use a robot centric velocity generation and control for the operators to control the differential-drive mobile robots, which makes the robot control difficult for the operators. Such robot-centric control can cause the increase of accidents and the decrease of work efficiency. The experimental results with a real differential-drive mobile robot testbed demonstrate the efficiency of operator-centric mobile robot control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.45-51
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• 2002

In this paper are presented dynamic modeling and path-tracking of differential drive wheeled-mobile robots(WMRs) having the limited drive-torques. Instantaneously coincident coordinate system, force/torque propagation and Newton's equilibrium law are used to induce the dynamic model. When drive-torques generated by inverse dynamics exceed the limitation, we make wheeled-mobile robots follow the reference path by modifying the planned reference trajectory with time-scaling method. The controller is introduced to compensate for error owing to modeling uncertainty and measurement noise. And simulation results prove that method proposed by this paper is efficient.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.532-535
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• 1997

This paper describes the design of a fuzzy-logic controller for a differential-drive mobile robots. This controller uses absolute position information to modify control parameters to compensate the orientation error. CC-Control method is compensated for the internal error by wheel encoders and the fuzzy-logic control provides compensation for external errors. The validities of the proposed scheme is evaluated using simulation.

• 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.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.352-362
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• 2014

In this paper, a fuzzy logic controller is designed for a DC motor which can be used for navigation control of mobile robots. These mobile robots can be used for agricultural, defense and assorted social applications. The robots used in these fields can reduce manpower, save human life and can be operated using remote control from a distant place. The developed fuzzy logic controller is used to control navigation speed and steering angle according to the desired reference position. Differential drive is used to control the steering angle and the speed of the robot. Two DC motors are connected with the rear wheels of the robot. They are controlled by a fuzzy logic controller to offer accurate steering angle and the driving speed of the robot. Its location is monitored using GPS (Global Positioning System) on a real time basis. IR sensors in the robot detect obstacles around the robot. The designed fuzzy logic controller has been implemented in a robot, which depicts that the robot could avoid obstacle as well as perform its operation efficiently with remote online control.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.251-259
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• 2023

In the path traveling of differential-drive robots, the steering controller plays an important role in determining the path-following performance. When a robot with a pure-pursuit algorithm is used to continuously drive a right-angled driving path in an unstructured environment without turning in place, the robot cannot accurately follow the right-angled path and stops driving due to the ground and motor load caused by turning. In the case of pure-pursuit, only the current robot position and the steering angle to the current target path point are generated, and the steering component does not reflect the speed plan, which requires improvement for precise path following. In this study, we propose a driving algorithm for differentially driven robots that enables precise path following by planning the driving speed using the radius of curvature and fusing the planned speed with the steering angle of the existing pure-pursuit controller, similar to the Model Predict Control control that reflects speed planning. When speed planning is applied, the robot slows down before entering a right-angle path and returns to the input speed when leaving the right-angle path. The pure-pursuit controller then fuses the steering angle calculated at each path point with the accelerated and decelerated velocity to achieve more precise following of the orthogonal path.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.39-47
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• 2014

Odometry using wheel encoders is one of the fundamental techniques for the pose estimation of wheeled mobile robots. However, odometry has a drawback that the position errors are accumulated when the travel distance increases. Therefore, position errors are required to be reduced using appropriate calibration schemes. The UMBmark method is the one of the widely used calibration schemes for two wheel differential drive robots. In UMBmark method, it is assumed that odometry error sources are independent. However, there is coupled effect of odometry error sources. In this paper, a new calibration scheme by considering the coupled effect of error sources is proposed. We also propose the test track design for the proposed calibration scheme. The numerical simulation and experimental results show that the odometry accuracy can be improved by the proposed calibration scheme.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.154-161
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• 2015

Conventional path tracking methods designed for two-wheeled differential drive robots are not suitable for omni-directional robots. In this study, we present a controller which can accomplish more accurate path tracking and orientation correction by exploiting the unconstrained movement capability of omni-directional robots. The proposed controller is proven to be stable using a Lyapunov stability criterion. Various experiments in real environments show that performance of path tracking and orientation correction has improved in the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.498-505
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• 2002

Reducing odometer errors caused by kinematic imperfections in wheeled mobile robots is imestigated. Wheel diameters and wheelbase are corrected by using encoders without landmarks. A new velocity trajectory is proposed that compensates for an orientation error due to acceleration- resolution constraints on motor controllers. Based on this velocity trajectory, the wheel velocity of one out of two driven wheels may be changed by the traveled distance of the mobile robot. It is shown that a wheeled mobile robot can't move along a straight line exactly, even if kinematic correction are achieved perfectly, and this phenomenon is attributable to acceleration-resolution constraints on motor controllers. We experiment on a wheeled mobile robot with 2 d.o.f. are used in the experiment to verify the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.457-462
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• 2005

An empirical way of a covariance matrix which expresses the odometry uncertainty of mobile robots is proposed. This method utilizes PC-method which removes systematic errors of odometry. Once the systematic errors are removed, the odometry error can be modeled using the Gaussian probability distribution, and the parameters of the distribution can be represented by the covariance matrix. Experimental results show that the method yields $5{\%}$ and $2.3{\%}$ offset for the synchro and differential drive robots.