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Home > Archive>Volume 52, Issue S1, 2024 >151-157. DOI:10.11908/j.issn.0253-374x.24722
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Fusion Localization Through Integrating GNSS/IMU/Camera based on Observability Analysis
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Affiliation:

1.School of Automotive Studies， Tongji University， Shanghai 201804， China;2.Clean Energy Automotive Engineering Center， Tongji University， Shanghai 201804， China;3.Department of Civil and Environmental Engineering， University of California， Los Angeles， Los Angeles， CA 90095， U.S.A. 4. Shanghai Gongji Technology Co.， Ltd.，Shanghai 201804， China. 5. College of Computer Science and Technology， Zhejiang University， Hangzhou 310027， China

Clc Number:

U426

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    Abstract:

    Accurate pose estimation is of paramount importance for intelligent vehicles， serving as the foundation for decision-making， planning， and control. To enhance the accuracy of heading estimation in vehicle pose， a novel fusion localization algorithm based on observability is proposed in this paper， utilizing GNSS （Global Navigation Satellite System）， IMU （Inertial Measurement Unit）， and vision sensors. Firstly， to assess the observability of the error state in the GNSS/IMU system， a novel method for relative observability analysis is introduced， revealing the existence of four weakly observable states within the traditional GNSS/IMU system. Subsequently， a fusion localization algorithm grounded in relative observability is proposed， utilizing the relative heading angle estimated by Visual Odometry. The experimental results indicate that the proposed localization algorithm achieves a maximum heading error of 2.76° and an RMS heading error of 1°， highlighting the effective enhancement of vehicle heading accuracy in weakly observable states by the proposed algorithm.

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LIU Wei, SONG Shunhui, XIA Xin, LU Yishi, LIU Changsheng, YU Zhuoping. Fusion Localization Through Integrating GNSS/IMU/Camera based on Observability Analysis[J].同济大学学报(自然科学版),2024,52(S1):151~157

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  • Received:September 28,2023
  • Online: November 20,2024
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