• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.493-495
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• 2004

In this paper, shows a research in accordance with the design the implementation of the localization system for mobile robot using INS(Inertial Navigation System) and GPS(Global Positioning System). First, a Strapdown Inertial Navigation System : SDINS is designed and implemented for low speed walking robot, by modifying Inertial Navigation System which is widely used for rocket, airplane, ship and so on. In addition, thesis proposes the localization of robot with the method of loosely coupled method by using Kalman Filter with INS/GPS integrated system to utilize assumed position and steed data from GPS.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.3
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• pp.308-315
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• 1991

This paper deals with the global dynamic behavior of multiple autonomous mobile robots with suggested navigation strategies within unbounded and bounded spatial domain. We derive some navigation strategies of robots wirh complete detectability with finite range to reach their goal states without collision which is motivated by Coulomb's law regarding repulsive and attractive forces between electrical charges. An analysis of the dynamic behavior of the interacting robots with the suggested navigation strategies under the assumption that communication is not permissible between robots is made and some examples are illustrated by computer simulation. The convergence of robot motions to their goal states under certain conditions is established by considering their global dynamic behavior even when some objects are close to their goal points.

• The Journal of Information Systems
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• v.18 no.2
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• pp.19-34
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• 2009

The purpose of this study is to analyze the influence of the flow concepts to the visitor's satisfaction in the mobile sensor-network navigation system. recently installed in the National Museum of Korea in Seoul. The satisfaction of visitor's on the facilities and services offered by the museum environment is crucial in that it provides a value-added learning experience for the visitor to immerse into the historical descriptions and cultural contents, often presented in digital formats. 200 subjects' data are analyzed using the structural equation model and the key results are presented. It is hoped thai our flow results show a new way of understanding of information technologies applied to the museum setting.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2393-2395
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• 2001

The mobile robot is used as an instrument of transportation in automated plant. But the greater part of the moving method is the wheel-type. The wheel-type robot is easier control than the track-type, However the track-type is better than the wheel-type in bad landform(bend landform, an incline plane, stairs). In this paper, we propose the navigation algorithm of track-type robot in order to improve a defect of wheel-type. We experiment in bend landfrom and even ground to differentiate the navigation method. To estimate robot pose, we use the 80196 in a close distance and the vision-board in a long distance. Each data is managed in main PC and then the part of managing correspond to every sensor. We also use twelve supersonic wave-sensors to recognize external surroundings. As the result of experiment, we analyze the algorithm of control and make possible surroundings-adaptation.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.605-613
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• 2013

This research proposes a vibration pattern algorithm to implement the haptic joystick to control a mobile robot at the remote site without watching the navigation environment. When the user cannot watch the navigation environment of the mobile robot, the user may rely on the haptic joystick solely to avoid obstacles and to guide the mobile robot to the target. To generate vibration patterns, there is a vibration motor at the bottom of the joystick which is held by the user to control the motion direction of the mobile robot remotely. When the mobile robot approaches to an obstacle, a pattern of vibration is generated by the motor, and by feeling the vibration pattern which is determined by the relative position of the mobile robot to the obstacle, the user can move the joystick to avoid the collision to the obstacle for the mobile robot. To generate the vibration patterns to convey the relative location of the obstacle near the mobile robot to the user, Fuzzy interferences have been utilized. To measure the distance and location of the obstacle near the mobile robot, ultrasonic sensors with the ring structure have been adopted and they are attached at the front and back sides of the mobile robot. The precise location of the obstacle is obtained by fusing the multiple data from ultrasonic sensors. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.726-734
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• 2007

Generally, a mobile robot is moved by original input programs. However, it is very hard for a non-expert to change the program generating the moving path of a mobile robot, because he doesn't know almost the teaching command and operating method for driving the robot. Therefore, the teaching method with speech command for a handicapped person without hands or a non-expert without an expert knowledge to generate the path is required gradually. In this study, for easily teaching the moving path of the autonomous mobile robot, the autonomous mobile robot with the function of speech recognition is developed. The use of human voice as the teaching method provides more convenient user-interface for mobile robot. To implement the teaching function, the designed robot system is composed of three separated control modules, which are speech preprocessing module, DC servo motor control module, and main control module. In this study, we design and implement a speaker dependent isolated word recognition system for creating moving path of an autonomous mobile robot in the unknown environment. The system uses word-level Hidden Markov Models(HMM) for designated command vocabularies to control a mobile robot, and it has postprocessing by neural network according to the condition based on confidence score. As the spectral analysis method, we use a filter-bank analysis model to extract of features of the voice. The proposed word recognition system is tested using 33 Korean words for control of the mobile robot navigation, and we also evaluate the performance of navigation of a mobile robot using only voice command.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1259-1263
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based wheeled mobile robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps have a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor. To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. But it is hard because of nonlinearity. Therefore, data set between position of WMR and features of lamps are configured. Neural network are composed and learned with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.558-565
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• 2011

Various robot platforms have been designed and developed to perform given tasks in a hazardous environment for surveillance, reconnaissance, search and rescue, etc. We considered a terrain-adaptive and transformable hybrid robot platform that is equipped with rapid navigation capability on flat floors and good performance in overcoming stairs or obstacles. The navigation mode transition is determined and implemented by adaptive driving mode control of the mobile robot. In order to maximize the usability of wheel-track hybrid robot platform, we propose a terrain-adaptive and user-friendly remote controller and verify the efficiency and performance through its navigation performance experiments in real and test-bed environments.

• 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.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.