• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.423-423
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• 2000

This paper proposes an effective algorithm for following a wall by an autonomous mobile robot with sonar sensors and infrared sensors in an indoor environment. The proposed method uses deadreckoning to estimate the current position and orientation of a mobile robot. Sonar sensor data are used to estimate shape and position of wall using proposed algorithm. Infrared sensor data are used as assistant when sonar sensor data is uncertain. Simulation results using mobile robot show that the proposed algorithm is proper for the following wall.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.42-48
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• 2011

It is very important for a mobile robot to recognize and model its environments for navigation. However, the grid map constructed by sonar sensors cannot accurately represent the environment, especially the narrow environment, due to the angular uncertainty of sonar data. Therefore, we propose a map building scheme which combines sonar sensors and IR sensors. The maps built by sonar sensors and IR sensors are combined with different weights which are determined by the degree of translational and rotational motion of a robot. To increase the effectiveness of sensor fusion, we also propose optimal sensor arrangement through various experiments. The experimental results show that the proposed method can represent the environment such as narrow corridor and open door more accurately than conventional sonar sensor-based map building methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.3-91
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• 2001

A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.386-392
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• 1990

This paper discribes a sonar-based certainty grid, the probabilistic representation of the uncertain and incomplete sensor knowledge, for autonomous mobile robot navigation. We use sonar sensor range data to build a map of the robot's surroundings. This range data provides information about the location of the objects which may exist in front of the sensor. From this information, we can compute the probability of being occupied and that of being empty for each cell. In this paper, a new method using Bayesian formula is introduced, which enables us to overcome some difficulties of the Ad-Hoc formula that has been the only way of updating the grids. This new formula can be applied to other kinds of sensors as well as sonar sensor. The validity of this formula in the real world is verified through simulation and experiment. This paper also shows that a wide angle sensor such as sonar sensor can be used effectively to identify the empty area, and the simultaneous use of multiple sensors and fusion in a certainty grid can improve the quality of the map.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.273-279
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• 2009

In this paper, we address the problem of detecting incorrect sonar measurements. We use ideas from the inconsistency of information among sonar measurements together with the sound pressure of the wave from the sonar sensor to develop a new method, called the comparison of the sound pressure (CSP), to detect incorrect sonar readings. The inconsistency of information in cells can be a clue that indicates candidates for incorrect measurements, and the sound pressure of the wave from the sonar sensor determines incorrect readings among the candidates. From various experiments, the proposed method is confirmed that it is better than existing method at deciding the state of sonar measurements.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1738-1741
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• 1997

This paper addresses the issue fo target classification and localization with a SONAR for mobiler robot indoor navigation. In particular, multiple refetions of SONAR sound are used actively and interntionally. As for the SONAR sensor, the multiple reflection has been generally considered as one of the noisy phenomena, which is inevitable in the indoor environments. However, these multiple reflections can be a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. This paper develops a new SONAR sensor module with a reflection plane which can actively create the multiple refection. This paper also intends to suggest a new target classification emthod which uses the multiple refectiions. We approximate the world as being two dimensional and assume that the targets consisting of the indoor environment are pland, corner, and edge. Multiple reflection paths of an acoustic bean by a SONAR are analyzed, by simulations and the patterns of the TOPs (Time Of Flight) and angles of multiple reflections from each target are also analyzed. In addition, a new algorithm for target classification and localization is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1219-1226
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• 2011

This paper proposes a novel approach to building an occupancy grid map using sonar data. It is very important for a mobile robot to recognize and construct its surrounding environments for navigation. However, the grid map constructed by ultrasonic sensors cannot represent a realistic shape of given environments due to incorrect sonar measurements caused by specular reflection. To overcome this problem, we propose an advanced sonar sensor model which consists of distance and shape factors used to determine the reliability of sensor data. Through this sensor model, a robot can build a high-quality grid map. The proposed method was verified by various experiments and showed that the robot could build an accurate map with sonar data in various indoor environments.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2337-2340
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• 2002

This paper presents the method of AGV(Automatic guided vehicle)'s moving environment(plane, corner, edge) recognition using SONAR sensor configuration. As for the SONAR sensor, the Crosstalk effect has been generally considered as an inevitable noisy phenomenon in the indoor environment. However, this effect can be used as a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. EERUF(error eliminate rapid ultrasonic firing) is a method for firing multiple ultrasonic sensors in mobile robot application and multi-echo mode of POLARIOD Device can reduce the Crosstalk effect. Here, Crosstalk effect was reduced using EERUF and applied to the AGV with a simple wall-following algorithm in the indoor environment. This method was tesed by a typical AGV with multi SONAR sensors in the laboratory environment.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.435-449
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• 2020

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.85-91
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• 2000

Underwater sensor accuracy test which measures the detection range and bearing accuracies of sonar simulates sonar transmitting ping and underwater radiating noise of target vessels. In this test, because the position of sonar target is the reference position of test, the sonar target position should be precisely estimated. Hence, this paper suggests to apply USBL algorithm which adopts cross phase spectrum of received sensor signals, and presents its performance by range and bearing estimation simulations. As a result of simulations, suggested algorithm shows good accuracy for underwater sensor accuracy test near 5㏈ SNR.