Wheel-INS2: Multiple MEMS IMU-based Dead Reckoning System with Different Configurations for Wheeled Robots

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Wheel-INS two: Multiple MEMS IMU-based Dead Reckoning System with Different Configurations for Wheeled Robots

Abstract-A reliable self-contained navigation system is essential for autonomous vehicles. Based on our previous study on Wheel-INS, a wheel-mounted inertial measurement unit (Wheel-IMU)-based dead reckoning (DR) system, in this paper, we propose a multiple IMUs-based DR solution for the wheeled robots. The IMUs are mounted at different places on the wheeled vehicles to acquire various dynamic information. In particular, at least one IMU has to be mounted at the wheel to measure the wheel velocity and take advantage of the rotation modulation. The system is implemented through a distributed extended Kalman filter structure where each subsystem (corresponding to each IMU) retains and updates its own states separately. The relative position constraints between the multiple IMUs are exploited to further limit the error drift and improve the system's robustness. Particularly, we present the DR systems using dual Wheel-IMUs, one Wheel-IMU plus one vehicle body-mounted IMU (Body-IMU), and dual Wheel-IMUs plus one Body-IMU as examples for analysis and comparison. Field tests illustrate that the proposed multi-IMU DR system outperforms the single Wheel-INS in terms of both positioning and heading accuracy. By comparing with the centralized filter, the proposed distributed filter shows unimportant accuracy degradation while holding significant computation efficiency. Moreover, among the three multi-IMU configurations, the one Body-IMU plus one Wheel-IMU design obtains the minimum drift rate. The position drift rates of the three configurations are zero point eight two percent (dual Wheel-IMUs), zero point six nine percent (one Body-IMU plus one Wheel-IMU), and zero point seven three percent (dual Wheel-IMUs plus one Body-IMU), respectively.

NOMENCLATURE

a) Matrices are denoted as uppercase bold letters b) Vectors are denoted as lowercase bold italic letters.

c) Scalars are denoted as lowercase italic letters.

d) Coordinate frames involved in the vector transformation are denoted as superscript and subscript. For vectors, the superscript denotes the projected coordinate system.

e) estimated or computed values.

f) observed or measured values.

One. INTRODUCTION

Two. RELEVANT WORK

B. Multiple IMUs Fusion

Three. Overview of the Proposed System

Four. Prerequisites

B. Error State Model

Five. Measurement Models

A. Wheel Velocity Measurement

B. Multi-IMU Position Constraint

Algorithm one Multi-IMU Position Constraint Measurement

Six. Experimental Results

A. Experimental Description

B. Performance Comparison

C. Discussion

Seven. CONCLUSION

Overview

The paper introduces the Wheel-INS2 system, which utilizes multiple MEMS IMUs for enhanced dead reckoning in wheeled robots. It analyzes different configurations of IMUs to minimize drift and improve positional accuracy, demonstrating via field tests that the proposed system outperforms traditional single-unit systems.

Key Points

1The proposed multi-IMU system provides better positioning and heading accuracy compared to single IMU systems
2Different IMU configurations were analyzed including dual and body-mounted IMUs
3Field tests showed significant improvements in accuracy with minimal drift rate
4A distributed extended Kalman filter structure is utilized for system implementation
5Integrating multiple IMUs allows for more robust navigation in GNSS-degraded environments.

Details

Authors: Yibin Wu, Jian Kuang, Xiaoji Niu
Category: Technology and Engineering

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