• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.421-432
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• 2013

This paper describes implementation of functions for mobile robot localization, which is one of the vital technologies for autonomous navigation of a mobile robot. There are several function libraries for mobile robot navigation. Some of them have limited applicability for practical use since they can be used only for simulation. Our research focuses on development of functions which can be used for localization of indoor robots. The functions implement deadreckoning and motion model of mobile robots, measurement model of range sensors, and frequently used calculations on angular directions. The functions encompass various types of robots and sensors. Also, various types of uncertainties in robot motion and sensor measurements are implemented so that the user can select proper ones for their use. The functions are tested and verified through simulation and experiments.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.532-535
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• 2022

Path following algorithms have been intensively studied for various mobile platforms such as planetary exploration, unmanned delivery, and autonomous driving. However, ensuring high accuracy in practical applications is challenging due to enormous uncertainty inherent in real environment. In this paper, we aim to reveal the guideline for the design and implementation by investigating the path following performance of mobile robot controlled by the pure pursuit algorithm. To this end, we evaluate the accuracy of the pure pursuit algorithm when tuning the look ahead distance and deploying erroneous actuator.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.361-368
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• 2015

This paper reports an unscented Kalman filter approach for localization of a mobile robot in an indoor environment. The method proposes a new model of measurement uncertainty which adjusts the error covariance according to the measured distance. The method also uses non-zero off diagonal values in error covariance matrices of motion uncertainty and measurement uncertainty. The method is tested through experiments in an indoor environment of 100*40 m working space using a differential drive robot which uses Laser range finder as an exteroceptive sensor. The results compare the localization performance of the proposed method with the conventional method which doesn't use adaptive measurement uncertainty model. Also, the experiment verifies the improvement due to non-zero off diagonal elements in covariance matrices. This paper contributes to implementing and evaluating a practical UKF approach for mobile robot localization.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.21-27
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• 2022

Traditional automobile or 2-wheeled robot have limitations on mobility because of their mechanical structure. As traditional automobile is being replaced by electric cars, robot technology is applied to the car industry. In robotics, many researchers worked on omnidirectional mobile robot and produced lots of noticeable results. However in many of the results, specialized wheels such as Mecanum wheels are required. That imposes restrictions on robot speed and outdoor driving. We proposed a 2-wheeled modular robot that has omnidirectional mobility without using specialized wheels. In this paper, we propose a 4-wheeled omnidirectional mobile robot that consists of those two modular robots. The proposed robot adopts electric brakes to combine wheel housings and the robot body or to separate wheel housings from the robot body. Two absolute-type encoders and four incremental encoders are used to control the position of the wheel housing and velocities of the wheels. The proposed robot has omnidirectional mobility and can move fast and outdoor with normal tire wheels. We implemented the proposed robot and the feasibility and stability of the robot is verified by two separate experiments.

• 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.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.32-39
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• 2022

Since the mobile platform and the manipulator mounted on it move at the same time in a mobile manipulator, the risk of mutual collision increases. Most of the studies on collision avoidance of mobile manipulators cannot be applied to differential drive type mobile platforms or the end-effector tends to deviate from the desired trajectory for collision avoidance. In this study, a collision avoidance algorithm based on null space projection (CANS) that solves these two problems is proposed. To this end, a modified repulsive force that overcomes the non-holonomic constraints of a mobile platform is generated by adding a virtual repulsive force in the direction of its instantaneous velocity. And by converting this repulsive force into a repulsive velocity and applying it to the null space, the end-effector of the robot avoids a collision while moving along its original trajectory. The proposed CANS algorithm showed excellent performance through self-collision avoidance tests and door opening tests.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.104-114
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• 1995

Mathematical models of industrial robots or manipulators are composed of highly nonlinear equations with nonlinear couplings between the variables of motions. These nonlin- earities were not considered important in the first stage that the working speed of the manipulator was not so fast, but the effect of nonlinear forces has become serious, as the working speed has been increased. So more improvement of performance cannot be expected by the control of manipulator using approximate linearization. As an approach for solving these problems, there is a method that eliminates nonlinear theory, which makes possible cecoupling of coupling terms and arbitrary arranging of poles is briefly introduced in this study. When the theory is applied to design the control law, its feasibility is examined whether the reasonable control results are obtained by simulating position, velocity, torque and tracing trajectory. The relations between the coefficients of the linearized differential equations and the maximum error and torque for the prescribed trajectory are also examined. Finally, the method for selecting the values for getting the most rapid and precise response within maximum torque of each drive is suggested in the choice of coefficients of characteristic equations which are obtained as a result of the control.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.471-476
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• 2015

This paper presents a maximum velocity trajectory planning algorithm for differential mobile robots with wheel velocity constraint to cope with physical limits in the joint space for two-wheeled mobile robots (TMR). In previous research, the convolution operator was able to generate a central velocity that deals with the physical constraints of a mobile robot while considering the heading angles along a smooth curve in terms of time-dependent parameter. However, the velocity could not track the predefined path. An algorithm is proposed to compensate an error that occurs between the actual and driven distance by the velocity of the center of a TMR within a sampling time. The velocity commands in Cartesian space are also converted to actuator commands to drive two wheels. In the case that the actuator commands exceed the maximum velocity the trajectory is redeveloped with the compensated center velocity. The new center velocity is obtained according to the curvature of the path to provide a maximum allowable velocity meaning a time-optimal trajectory. The effectiveness of the algorithm is shown through numerical examples.