• Title/Summary/Keyword: laser inertial measurement unit

Search Result 15, Processing Time 0.029 seconds

Evaluating LIMU System Quality with Interval Evidence and Input Uncertainty

  • Xiangyi Zhou;Zhijie Zhou;Xiaoxia Han;Zhichao Ming;Yanshan Bian
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.11
    • /
    • pp.2945-2965
    • /
    • 2023
  • The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

The Six-Position Calibration Technique of Gyro Bias for Rotational Inertial Navigation System Based on Ring Laser Gyroscope (링 레이저 자이로 기반 회전형 관성항법장치를 위한 6-자세 자이로 바이어스 교정 방법)

  • Yu, Haesung;Kim, Cheon-Joong;Lee, Inseop;Oh, Ju-Hyun;Sung, Chang-Ky;Lee, Sangjeong
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.22 no.2
    • /
    • pp.189-196
    • /
    • 2019
  • The inertial sensor errors in SDINS(Strapdown Inertial Navigation System) can be compensated by rotating the inertial measurement unit and it is called RINS(Rotational Inertial Navigation System). It is assumed that the error of the inertial sensor in RINS is a static bias. However, the error of the inertial sensor actually developed and produced is not a static bias due to the change of the temperature applied to the sensor and the influence of the earth's gravity acceleration. In this paper, we propose a six-position gyro bias calibration method to evaluate the gyro bias required for RINS and present the test results of applying it to a ring laser gyro inertial navigation system under development.

Real-time Recognition of the Terrain Configuration to Increase Driving Stability for Unmanned Robots (안정성 향상을 위한 자율 주행 로봇의 실시간 접촉 지면 형상인식)

  • Jeon, Bongsoo;Kim, Jayoung;Lee, Jihong
    • The Journal of Korea Robotics Society
    • /
    • v.8 no.4
    • /
    • pp.283-291
    • /
    • 2013
  • Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Acquisition of 3D Spatial Data for Indoor Environment by Integrating Laser Scanner and CCD Sensor with IMU (실내 환경에서의 3차원 공간데이터 취득을 위한 IMU, Laser Scanner, CCD 센서의 통합)

  • Suh, Yong-Cheol;Nagai, Masahiko
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.10 no.1
    • /
    • pp.1-9
    • /
    • 2007
  • 3D data are in great demand for pedestrian navigation recently. For pedestrian navigation, we needs to reconstruct 3D model in detail from people's eye. In order to present spatial features in detail for pedestrian navigation, it is indispensable to develop 3D model not only in outdoor environment but also in indoor environment such as underground shopping complex. However, it is very difficult to acquire 3D data efficiently by mobile mapping without GPS. In this research, 3D shape was acquired by Laser scanner, and texture by CCD(Charge Coupled Device) sensor. Continuous changes position and attitude of sensors were measured by IMU(Inertial Measurement Unit). Moreover, IMU was corrected by relative orientation of CCD images without GPS(Global Positioning System). In conclusion, Reliable, quick, and handy method for acquiring 3D data for indoor environment is proposed by a combination of a digital camera and a laser scanner with IMU.

  • PDF

A Study on Error Analysis of Dual-Axis Rotational Inertial Navigation System Based on Ring Laser Gyroscope (링레이저 자이로 기반 2축 회전형 관성항법장치 오차해석에 대한 연구)

  • Kim, Cheon-Joong;Yu, Hae-Sung;Lee, In-Seop;Oh, Ju-Hyun;Lee, Sang-Jeong
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.46 no.11
    • /
    • pp.921-933
    • /
    • 2018
  • There is a method to enhance the pure navigation performance of INS(Inertial Navigation System) through the rotation of inertial measurement unit to compensate error sources of inertial sensors each other and that INS using this principle of operation is called rotational INS. In this paper, the exact error analysis of rotational INS based on ring laser gyro considering the coupling effect with gravity and earth rate is performed to evaluate the navigation performance by inertial sensor error sources. And error analysis and performance evaluation result confirmed by modelling and simulation is also proposed in this paper.

Integration and Synchronization of Multi Sensors for Mobile Mapping System (모바일 매핑시스템을 위한 멀티 센서 통합 및 동기화 구현 방안 연구)

  • Park, Young-Moo;Lee, Jong-Ki;Sung, Jeong-Gon;Kim, Byung-Guk
    • Journal of Korea Spatial Information System Society
    • /
    • v.6 no.1 s.11
    • /
    • pp.51-58
    • /
    • 2004
  • Mobile Mapping System is an effective wav to obtain position and image using vehicle equipped with GPS(Global Positioning System), IMU(Inertial Measurement Unit), and CCD camera. It have been used various fields of load facility management, map upgrade and etc. It is difficult to upgrade Mobile Mopping System which is developed from abroad and add other sensors because we don't know the way to integrate and synchronize multi-sensors. In this paper, we present the effective way of the integration and synchronization method for multi sensors we designed and manufactured Synchronization equipment by considering sensors of laser, odometer and etc.

  • PDF

Autonomous Navigation of KUVE (KIST Unmanned Vehicle Electric) (KUVE (KIST 무인 주행 전기 자동차)의 자율 주행)

  • Chun, Chang-Mook;Suh, Seung-Beum;Lee, Sang-Hoon;Roh, Chi-Won;Kang, Sung-Chul;Kang, Yeon-Sik
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.16 no.7
    • /
    • pp.617-624
    • /
    • 2010
  • This article describes the system architecture of KUVE (KIST Unmanned Vehicle Electric) and unmanned autonomous navigation of it in KIST. KUVE, which is an electric light-duty vehicle, is equipped with two laser range finders, a vision camera, a differential GPS system, an inertial measurement unit, odometers, and control computers for autonomous navigation. KUVE estimates and tracks the boundary of road such as curb and line using a laser range finder and a vision camera. It follows predetermined trajectory if there is no detectable boundary of road using the DGPS, IMU, and odometers. KUVE has over 80% of success rate of autonomous navigation in KIST.

Development of Digital Surface Model and Feature Extraction by Integrating Laser Scanner and CCD sensor

  • Nagai, Masahiko;Shibasaki, Ryosuke;Zhao, Huijing;Manandhar, Dinesh
    • Proceedings of the KSRS Conference
    • /
    • 2003.11a
    • /
    • pp.859-861
    • /
    • 2003
  • In order to present a space in details, it is indispensable to acquire 3D shape and texture simultaneously from the same platform. 3D shape is acquired by Laser Scanner as point cloud data, and texture is acquired by CCD sensor. Positioning data is acquired by IMU (Inertial Measurement Unit). All the sensors and equipments are assembled on a hand-trolley. In this research, a method of integrating the 3D shape and texture for automated construction of Digital Surface Model is developed. This Digital Surface Model is applied for efficient feature extraction. More detailed extraction is possible , because 3D Digital Surface Model has both 3D shape and texture information.

  • PDF

Effective Reduction of Horizontal Error in Laser Scanning Information by Strip-Wise Least Squares Adjustments

  • Lee, Byoung-Kil;Yu, Ki-Yun;Pyeon, Moo-Wook
    • ETRI Journal
    • /
    • v.25 no.2
    • /
    • pp.109-120
    • /
    • 2003
  • Though the airborne laser scanning (ALS) technique is becoming more popular in many applications, horizontal accuracy of points scanned by the ALS is not yet satisfactory when compared with the accuracy achieved for vertical positions. One of the major reasons is the drift that occurs in the inertial measurement unit (IMU) during the scanning. This paper presents an algorithm that adjusts for the error that is introduced mainly by the drift of the IMU that renders systematic differences between strips on the same area. For this, we set up an observation equation for strip-wise adjustments and completed it with tie point and control point coordinates derived from the scanned strips and information from aerial photos. To effectively capture the tie points, we developed a set of procedures that constructs a digital surface model (DSM) with breaklines and then performed feature-based matching on strips resulting in a set of reliable tie points. Solving the observation equations by the least squares method produced a set of affine transformation equations with 6 parameters that we used to transform the strips for adjusting the horizontal error. Experimental results after evaluation of the accuracy showed a root mean squared error (RMSE) of the adjusted strip points of 0.27 m, which is significant considering the RMSE before adjustment was 0.77 m.

  • PDF

Traveling Performance of a Robot Platform for Unmanned Weeding in a Dry Field (벼농사용 무인 제초로봇의 건답환경 주행 성능)

  • Kim, Gook-Hwan;Kim, Sang-Cheol;Hong, Young-Ki
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.31 no.1
    • /
    • pp.43-50
    • /
    • 2014
  • This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.