• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.613-620
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• 2013

A new remote control algorithm for a mobile robot is proposed, where a remote controller consists of a camera and inertial sensors. Initially the relative position and orientation of a robot is estimated by capturing four circle landmarks on the plate of the robot. When the remote controller moves to point to the destination, the camera pointing trajectory is estimated using an inertial navigation algorithm. The destination is transmitted wirelessly to the robot and then the robot is controlled to move to the destination. A quick movement of the remote controller is possible since the destination is estimated using inertial sensors. Also unlike the vision only control, the robot can be out of camera's range of view.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.98-102
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• 2015

This paper proposes an autonomous navigation method for a nonholonomic mobile robot, based on the generalized Voronoi diagram (GVD). We define the look-ahead point for a given motion constraint to determine the direction of motion, which solves the problem of a minimum turning radius for the real nonholonomic mobile robot. This method can be used to direct the robot to explore an unknown environment and construct smooth feedback curves for the nonholonomic robot. As the trajectories can be smoothed, the position of the robot can be stabilized in the plane. The simulation results are presented to verify the performance of the proposed methods for the nonholonomic mobile robot. Furthermore, this approach is worth drawing on the experience of any other mobile robots.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.218-224
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• 2009

This paper proposes an effective SLAM based on redundant extended Kalman filter for robot navigation in an irregular surface to enhance the accuracy of robot's pose. To establish an accurate model of a caterpillar type robot is very difficult due to the mechanical complexity of the system which results in highly nonlinear behavior. In addition, for robot navigation on an irregular surface, its control suffers from the uncertain pose of the robot heading closely related to the condition of the floor. We show how this problem can be overcome by the proposed approach based on redundant extended Kalman filter through some computer simulation results.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.118-123
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• 2023

This study presents sensor system for autonomous mobile robot capable of floor-to-floor self-navigation. The robot was modified using the Turtlebot3 hardware platform and ROS2 (robot operating system 2). The robot utilized the Navigation2 package to estimate and calibrate the moving path acquiring a map with SLAM (simultaneous localization and mapping). For elevator boarding, ultrasonic sensor data and threshold distance are compared to determine whether the elevator door is open. The current floor information of the elevator is determined using image processing results of the ceiling-fixed camera capturing the elevator LCD (liquid crystal display)/LED (light emitting diode). To realize seamless communication at any spot in the building, the LoRa (long-range) communication module was installed on the self-navigating autonomous mobile robot to support the robot in deciding if the elevator door is open, when to get off the elevator, and how to reach at the destination.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.315-322
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• 2009

This paper explains a control and navigation algorithm of a 6-DOF gait rehabilitation robot, which can allow a patient to navigate in virtual reality (VR) by upper and lower limbs interactions. In gait rehabilitation robots, one of the important concerns is not only to follow the robot motions passively, but also to allow the patient to walk by his/her intention. Thus, this robot allows automatic walking velocity update by estimating interaction torques between the human and the upper limb device, and synchronizing the upper limb device to the lower limb device. In addition, the upper limb device acts as a user-friendly input device for navigating in virtual reality. By pushing the switches located at the right and left handles of the upper limb device, a patient is able to do turning motions during navigation in virtual reality. Through experimental results of a healthy subject, we showed that rehabilitation training can be more effectively combined to virtual environments with upper and lower limb connections. The suggested navigation scheme for gait rehabilitation robot will allow various and effective rehabilitation training modes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.696-702
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• 2015

This paper suggests a new method for making a navigation path by using Bezier curve in order to improve the navigation performance used to avoid obstacles during a robot soccer game. We analyzed the advantages and disadvantages of both vector-field and limit-cycle navigation methods, which are the mostly widely used navigation methods for avoiding obstacles. To improve the disadvantages of these methods, we propose a new design technique for generating a more proper path using Bezier curve and describe its advantages. Using computer simulations and experiments, we compare the performance of vector-field navigation with that of Bezier curve navigation. The results prove that the navigation performance using Bezier curve is relatively superior to the other method.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.226-234
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• 2016

In this study, a model-referenced underwater navigation algorithm is proposed for high-precise underwater navigation using monocular vision near underwater structures. The main idea of this navigation algorithm is that a 3D model-based pose estimation is combined with the inertial navigation using an extended Kalman filter (EKF). The spatial information obtained from the navigation algorithm is utilized for enabling the underwater robot to navigate near underwater structures whose geometric models are known a priori. For investigating the performance of the proposed approach the model-referenced navigation algorithm was applied to an underwater robot and a set of experiments was carried out in a water tank.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.