• Title/Summary/Keyword: Sonar Sensors

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EKF-based SLAM Using Sonar Salient Feature and Line Feature for Mobile Robots (이동로봇을 위한 Sonar Salient 형상과 선 형상을 이용한 EKF 기반의 SLAM)

  • Heo, Young-Jin;Lim, Jong-Hwan;Lee, Se-Jin
    • Journal of the Korean Society for Precision Engineering
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    • v.28 no.10
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    • pp.1174-1180
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    • 2011
  • Not all line or point features capable of being extracted by sonar sensors from cluttered home environments are useful for simultaneous localization and mapping (SLAM) due to their ambiguity because it is difficult to determine the correspondence of line or point features with previously registered feature. Confused line and point features in cluttered environments leads to poor SLAM performance. We introduce a sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The reliable line feature is expressed by its end points and engaged togather in EKF SLAM to overcome the geometric limits and maintain the map consistency. Experimental results demonstrate the validity and robustness of the proposed method.

Grid Map Building through Neighborhood Recognition Factor of Sonar Data (초음파 데이터의 형상 인지 지수를 이용한 확률 격자 지도의 작성)

  • Lee, Se-Jin;Park, Byung-Jae;Lim, Jong-Hwan;Chung, Wan-Kyun;Cho, Dong-Woo
    • The Journal of Korea Robotics Society
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    • v.2 no.3
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    • pp.227-233
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    • 2007
  • Representing an environment as the probabilistic grids is effective to sense outlines of the environment in the mobile robot area. Outlines of an environment can be expressed factually by using the probabilistic grids especially if sonar sensors would be supposed to build an environment map. However, the difficult problem of a sonar such as a specular reflection phenomenon should be overcome to build a grid map through sonar observations. In this paper, the NRF(Neighborhood Recognition Factor) was developed for building a grid map in which the specular reflection effect is minimized. Also the reproduction rate of the gird map built by using NRF was analyzed with respect to a true map. The experiment was conducted in a home environment to verify the proposed technique.

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Analysis of the range estimation error of a target in the asynchronous bistatic sonar (비동기 양상태 소나의 표적 거리 추정 오차 분석)

  • Jeong, Euicheol;Kim, Tae-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.3
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    • pp.163-169
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    • 2020
  • The asynchronous bistatic sonar needs to estimate direct blast arrival time at a receiver to localize targets, and therefore the direct blast arrival time estimation error could be added to target localization error in comparison with synchronous system. Direct blast especially appears as several peaks at the matched filter output by multipath, thus we compared the first peak detection technique and the maximum peak detection technique of those peaks for direct blast arrival time estimation through sea trial data. The test was performed in a shallow sea with bistatic sonar made up of spatially separated source and line array sensors. Line array sensors obtained the target signal which is generated from the echo repeater. As a result, the first peak detection technique is superior to maximum peak detection technique in direct blast arrival time estimation error. The result of this analysis will be used for further research of target tracking in the asynchronous bistatic sonar.

Comparative Analysis of the Performance of Robot Sensors in the MSRDS Platform (MSRDS 플랫폼에서 로봇 센서들의 성능 비교분석)

  • Lee, Jeong-Won;Chung, Jong-In
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.5
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    • pp.57-68
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    • 2014
  • MSRDS(Microsoft Robotics Developer Studio), the robot simulation platform provides the simulation robots and environments enabling to the basic robot programming without hardware robots. In this paper, we carry the maze escaping problems to compare and analyze the performance of LRF, bumper, IR, and sonar sensor with the same condition on MSRDS(Microsoft Robotics Developer Studio) environment. To evaluate the performance of sensors, we program the simulation environments with same conditions for all sensors. We could find that the LRF sensor had the highest performance and the bumper sensor has the lowest performance on the travel time, the number of turning, and the number of collisions. It was also confirmed that IR sensor and sonar sensor had lower performance than LRF sensor on the number of turning.

Sonar Map Construction Based on Acoustics Theory for Autonomous Mobile Robots (음향학에 기반한 자율이동로봇의 초음파 확률격자지도 작성)

  • Lee Y.C.;Lee S.J.;Lim J.H.;Cho D.W.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.400-403
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    • 2005
  • The sonar sensors can be divided into a piezo type and an electrostatic type according to a principle of an operating system. The electrostatic type of a sonar sensor is used for map building in this paper. If we know the characteristics of sonar sensor, we can derive the ultrasonic pressure equation from an acoustics theory. We, therefore, developed Ultrasonic Pressure Probabilistic Model (UPPM) to consider the sound pressure in the probability updating process. In this paper, we found that the quality of the resulting probability map is considerably improved, through combining the UPPM with the grid-based mapping algorithm.

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A Hybrid Navigation System for Underwater Unmanned Vehicles, Using a Range Sonar (초음파 거리계를 이용한 무인잠수정의 수중 복합 항법시스템)

  • LEE PAN-MOOK;JEON BONG-HWAN;KIM SEA-MOON;LEE CHONG-MOO;LIM YONG-KON;YANG SEUNG-IL
    • Journal of Ocean Engineering and Technology
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    • v.18 no.4 s.59
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    • pp.33-39
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    • 2004
  • This paper presents a hybrid underwater navigation system for unmanned underwater vehicles, using an additional range sonar, where the navigation system is based on inertial and Doppler velocity sensors. Conventional underwater navigation systems are generally based on an inertial measurement unit (IMU) and a Doppler velocity log (DVL), accompanying a magnetic compass and a depth sensor. Although the conventional navigation systems update the bias errors of inertial sensors and the scale effects of DVL, the estimated position slowly drifts as time passes. This paper proposes a measurement model that uses the range sonar to improve the performance of the IMU-DVL navigation system, for extended operation of underwater vehicles. The proposed navigation model includes the bias errors of IMU, the scale effects of VL, and the bias error of the range sonar. An extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation, when the external measurements are available. To illustrate the effectiveness of the hybrid navigation system, simulations were conducted with the 6-d.o.f. equations of motion of an AUV in lawn-mowing survey mode.

Map-Building and Position Estimation based on Multi-Sensor Fusion for Mobile Robot Navigation in an Unknown Environment (이동로봇의 자율주행을 위한 다중센서융합기반의 지도작성 및 위치추정)

  • Jin, Tae-Seok;Lee, Min-Jung;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.5
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    • pp.434-443
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    • 2007
  • Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

Development of Target Signal Simulator for Towed Line Array Sonar (선배열 예인음탐기 표적신호 시뮬레이터 개발)

  • Son, Kweon;Choi, Jae-Yong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.6 no.3
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    • pp.36-43
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    • 2003
  • Multi-target away signal simulator which can simulate the radiated noises of maneuvering targets in a specified ocean range is an essential equipment for the validation of developed towed array sonar system. This simulator should provide realistic multi-channel signals those are required for beamforming on the signal processing unit of towed away system. This paper describes the overall system configuration and signal synthesis techniques for the target radiated noise. And this paper considers why the time delays between target and individual sensors are caused and how to compensate these time delays to individual sensors output. This multi-purpose target simulator could be used for the training of TASS operators.

Development of a New Navigation Technology for Mobile Robot Based on Sonar Sensors (초음파센서 기반 이동로봇의 새로운 네비게이션 기술 개발)

  • Nguyen, Van-Quyet;Han, Sung-Hyun
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.18 no.6
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    • pp.664-674
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    • 2009
  • This paper presents the theoretical development of a complete navigation problem of a non-holonomic mobile robot by using sonar sensors. To solve this problem, a new method to compute a fuzzy perception of the environment is presented, dealing with the uncertainties and imprecision from the sensory system and taking into account nonholonomic constraints of the robot. Fuzzy perception, fuzzy controller are applied, both in the design of each reactive behavior and solving the problem of behavior combination, to implement a fuzzy behavior-based control architecture. Different experiments in populated environments have proved to be very successful. Our method is able to guide the mobile robot named KUM-Robo safety and efficiently during long experimental time.

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A quantitative analysis of synthetic aperture sonar image distortion according to sonar platform motion parameters (소나 플랫폼의 운동 파라미터에 따른 합성개구소나 영상 왜곡의 정량적 분석)

  • Kim, Sea-Moon;Byun, Sung-Hoon
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.4
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    • pp.382-390
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    • 2021
  • Synthetic aperture sonars as well as side scan sonars or multibeam echo sounders have been commercialized and are widely used for seafloor imaging. In Korea related research such as the development of a towed synthetic aperture sonar system is underway. In order to obtain high-resolution synthetic aperture sonar images, it is necessary to accurately estimate the platform motion on which it is installed, and a precise underwater navigation system is required. In this paper we are going to provide reference data for determining the required navigation accuracy and precision of navigation sensors by quantitatively analyzing how much distortion of the sonar images occurs according to motion characteristics of the platform equipped with the synthetic aperture sonar. Five types of motions are considered and normalized root mean square error is defined for quantitative analysis. Simulation for error analysis with parameter variation of motion characteristics results in that yaw and sway motion causes the largest image distortion whereas the effect of pitch and heave motion is not significant.