• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.339-346
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• 2006

Increased usage of autonomous underwater vehicle (AUV) has led to the development of alternative navigational methods that do not employ the acoustic beacons and dead reckoning sensors. This paper describes a simultaneous localization and mapping (SLAM) scheme that uses range sonars mounted on a small AUV. The SLAM is one of such alternative navigation methods for measuring the environment that the vehicle is passing through and providing relative position of AUV by processing the data from sonar measurements. A technique for SLAM algorithm which uses several ranging sonars is presented. This technique utilizes an unscented Kalman filter to estimate the locations of the AUV and objects. In order for the algorithm to work efficiently, the nearest neighbor standard filter is introduced as the algorithm of data association in the SLAM for associating the stored targets the sonar returns at each time step. The proposed SLAM algorithm is tested by simulations under various conditions. The results of the simulation show that the proposed SLAM algorithm is capable of estimating the position of the AUV and the object and demonstrates that the algorithm will perform well in various environments.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.61-69
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• 2005

This paper presents an efficient method of extracting line segments from the occupancy grids in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities using sonar sensors. We evaluate the orientation information of every grid when the occupancy probability of the grid is updated from sonar range data. To find the shape of an object in the map from orientation information, the orientations are clustered into several groups according to their values. The line segments are, then, extracted from the clusters based on Hough transform. Finally, a feature-based map is built with these line segments. The proposed method is illustrated with the results produced by sets of experiments in an indoor environment.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.177-182
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• 2004

In sonar sensor design impedance matching design to each sensor affects the whole weighting circuit characteristic very much. But there are many examples that it is made by hands or very simple modeling designs. So these design works make trial and error because it is the limitation of flexible correspondence to the many sensors and follows many errors. This study explains organizations and skills in the sensor modeling package design program with real sonar sensor characteristic measure as the first step in impedance matching design.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.779-784
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• 2004

This paper describes a sonic polygonal multiple reflection range sensor (SPMRS), which uses multiple reflection properties usually ignored in ultrasonic sensors as disturbances or noises. Targets such as a plane, corner, edge, or cylinder in indoor environments can easily be detected by the multiple reflection patterns obtained with a SPMRS system. Target classification and feature data extraction, such as distance and azimuth to the target, are computed simultaneously by considering the geometrical relationships between the detected targets, and finally the environment model is generated by refining the detected targets. In addition, the narrow field of view of a sonar range sensor is increased and the scanning time is reduced by active motion of the SPMRS stepping servomechanism.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.2
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• pp.15-22
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• 2005

This paper represents the sensor combination technique of mobile robot to reduce the ambiguity and uncertainty of environment that prevents the mobile robot from recognizing the path planning and navigation. The sensors such as optical encoder, ultra sonar sensor, and infra-red sensor gathered the dynamic information of mobile robot that are used to detect the obstacle. Therefore, the mobile robot controller with sensor combination is stably demonstrated by the experimental results.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.83-85
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• 2005

Exploration involving mapping and localization in an unknown environment is an important task in mobile robots. For this, robot must be able to build a reliable map of surroundings and to estimate the position of it. In this paper, we developed technique for gird-based localization of a mobile robot with ultrasonic sensors using EKF(Extended Kalman Filter). We also describe the information about landmarks detected in the environment. Finally, the robot experiments show the efficiency of our approach in the real environment.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.830-835
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• 2003

This paper describes a sonic polygonal multiple reflection range sensor (SPMRS), which uses multiple reflection properties usually ignored in ultrasonic sensors as disturbances or noises. Targets such as a plane, corner, edge, or cylinder in indoor environments can easily be detected by the multiple reflection patterns obtained with a SPMRS system. Target classification and feature data extraction, such as distance and azimuth to the target, are computed simultaneously by considering the geometrical relationships between the detected targets, and finally the environment model is generated by refining the detected targets. In addition, the narrow field of view of a sonar range sensor is increased and the scanning time is reduced by active motion of the SPMRS stepping servomechanism.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.313-319
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• 2023

In this study, we propose a method to improve the accuracy of acoustic odometry using optimal frame interval selection for Fourier-based image registration. The accuracy of acoustic odometry is related to the phase correlation result of image pairs obtained from the forward-looking sonar (FLS). Phase correlation failure is caused by spurious peaks and high-similarity image pairs that can be prevented by optimal frame interval selection. We proposed a method of selecting the optimal frame interval by analyzing the factors affecting phase correlation. Acoustic odometry error was reduced by selecting the optimal frame interval. The proposed method was verified using field data.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.888-891
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• 1991

In this paper, we have shown a new approach of neural networks for mobile robot motion control under an indoor refracted environment. The vehicle has two powered wheels and four passive casters which support a free motion. And it also uses sonar sensors, infrared sensors, Internal odometer, and contact sensors. Two experiments were conducted to demonstrate our objectives. The first one is that the vehicle executes a reflexive motor control to maintain a constant distance to the boundary. The second one is that as well as the boundary following, the vehicle makes a block obstacle avoidance during its path. Without prior knowledge of external environment. we have accomplished the tasks by employing a simple, reactive stimulus-response neural network scheme associating sensor data with the vehicle's action.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.37-42
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• 2013

In this paper, a localization algorithm and an autonomous controller for PETASUS system II which is an underwater vehicle-manipulator system, are proposed. To estimate its position and to identify manipulation targets in a structured environment, a multi-rate extended Kalman filter is developed, where map information and data from inertial sensors, sonar sensors, and vision sensors are used. In addition, a three layered control structure is proposed as a controller for autonomy. By this controller, PETASUS system II is able to generate waypoints and make decisions on its own behaviors. Experiment results are provided for verifying proposed algorithms.