JRM Vol.35 No.2 pp. 387-397
doi: 10.20965/jrm.2023.p0387


Localization System for Vehicle Navigation Based on GNSS/IMU Using Time-Series Optimization with Road Gradient Constrain

Aoki Takanose*, Kaito Kondo**, Yuta Hoda**, Junichi Meguro**, and Kazuya Takeda*

*Graduate School of Informatics, Nagoya University
Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8603, Japan

**Department of Mechatronics Engineering, Graduate School of Science and Technology, Meijo University
1-501 Shiogamaguchi, Tempaku-ku, Nagoya, Aichi 468-8502, Japan

October 21, 2022
January 18, 2023
April 20, 2023
autonomous mobile robot, localization, GNSS/IMU, urban environment, low cost sensors

In this paper, we propose a GNSS/IMU localization system for mobile robots when wheel speed sensors cannot be attached. Highly accurate location information is required for autonomous navigation of mobile robots. A typical method of acquiring location information is to use a Kalman filter for position estimation. The Kalman filter is a maximum-likelihood estimation method that assumes normally distributed noise. However, non-normally distributed GNSS multipath noise that frequently occurs in urban environments causes the Kalman filter to break down, and degrades the estimation performance. Other GNSS/IMU localization methods capable of lane-level estimation in urban environments use wheel speed sensors, which are unsuitable for the present situation. In this study, we aim to improve the performance of lane-level localization by adding a vehicle speed estimation function to adapt the method to those requiring wheel speed sensors. The proposed method optimizes time-series data to accurately compensate for accelerometer bias errors and reduce GNSS multipath noise. The evaluation confirmed the effectiveness of the proposed method, with improved velocity and position estimation performance compared with the Kalman filter method.

Block diagram of the proposed method

Block diagram of the proposed method

Cite this article as:
A. Takanose, K. Kondo, Y. Hoda, J. Meguro, and K. Takeda, “Localization System for Vehicle Navigation Based on GNSS/IMU Using Time-Series Optimization with Road Gradient Constrain,” J. Robot. Mechatron., Vol.35 No.2, pp. 387-397, 2023.
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