Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry

Xiaolong Zhang; Henri Liikanen; Eelis Peltola; Mohammad M. Aref; Jouni Mattila

doi:10.1007/978-3-030-85318-1_67

Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry

Xiaolong Zhang
, Henri Liikanen
, Eelis Peltola
, Mohammad M. Aref
, Jouni Mattila

Automation Technology and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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Abstract

We introduce a localization algorithm that uses an inertial measurement unit (IMU) and wheel odometry on a four-wheel-drive heavy vehicle for positioning. While wheel odometry alone works in simple cases without slippage, in cases that feature wheel slippage, the velocities measured by the wheel rotation show higher values. In the case of side slippage, the wheel sensors cannot observe the values. Therefore, IMUs are suitable for fusion with wheel odometry to generate real-time feedback. We use an error state Kalman filter (ESKF) to fuse the sensor information from an IMU with wheel odometry, showing results on a slow-manoeuvring vehicle in tests up to five minutes in length. The IMU is an industry-grade micro-electro mechanical system (MEMS) with a gyroscope featuring 6°/h bias in-run stability. We use a real-time kinematic global positioning system (RTK)-GPS as a ground truth reference for the vehicle’s heading angle and position. The tests results show our navigation has an accuracy of 0.3 m for position and 0.6° for heading angle, both within the root mean square error (RMSE) criteria. Our analysis shows that the nonlinearity of the gyroscope in the heading rotation axis is the key factor for improving performance in our implementation.

Original language	English
Title of host publication	15th European Workshop on Advanced Control and Diagnosis (ACD 2019)
Subtitle of host publication	Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019
Editors	Elena Zattoni, Silvio Simani, Giuseppe Conte
Publisher	Springer
Pages	1155-1172
Number of pages	18
ISBN (Electronic)	978-3-030-85318-1
ISBN (Print)	978-3-030-85317-4
DOIs	https://doi.org/10.1007/978-3-030-85318-1_67
Publication status	Published - 2022
Publication type	A4 Article in conference proceedings
Event	European Workshop on Advanced Control and Diagnosis - Bologna, Italy Duration: 21 Nov 2019 → 22 Nov 2019

Publication series

Name	Lecture Notes in Control and Information Sciences - Proceedings
Publisher	Springer
ISSN (Print)	2522-5383
ISSN (Electronic)	2522-5391

Conference

Conference	European Workshop on Advanced Control and Diagnosis
Country/Territory	Italy
City	Bologna
Period	21/11/19 → 22/11/19

Publication forum classification

Publication forum level 0

Access to Document

10.1007/978-3-030-85318-1_67

Localisation of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry - ACD19
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Zhang, X., Liikanen, H., Peltola, E., Aref, M. M., & Mattila, J. (2022). Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. In E. Zattoni, S. Simani, & G. Conte (Eds.), 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) : Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019 (pp. 1155-1172). (Lecture Notes in Control and Information Sciences - Proceedings). Springer. https://doi.org/10.1007/978-3-030-85318-1_67

Zhang, Xiaolong ; Liikanen, Henri ; Peltola, Eelis et al. / Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) : Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019. editor / Elena Zattoni ; Silvio Simani ; Giuseppe Conte. Springer, 2022. pp. 1155-1172 (Lecture Notes in Control and Information Sciences - Proceedings).

@inproceedings{eada50bf2b104d4ca9bd5b755ca19da0,

title = "Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry",

abstract = "We introduce a localization algorithm that uses an inertial measurement unit (IMU) and wheel odometry on a four-wheel-drive heavy vehicle for positioning. While wheel odometry alone works in simple cases without slippage, in cases that feature wheel slippage, the velocities measured by the wheel rotation show higher values. In the case of side slippage, the wheel sensors cannot observe the values. Therefore, IMUs are suitable for fusion with wheel odometry to generate real-time feedback. We use an error state Kalman filter (ESKF) to fuse the sensor information from an IMU with wheel odometry, showing results on a slow-manoeuvring vehicle in tests up to five minutes in length. The IMU is an industry-grade micro-electro mechanical system (MEMS) with a gyroscope featuring 6°/h bias in-run stability. We use a real-time kinematic global positioning system (RTK)-GPS as a ground truth reference for the vehicle{\textquoteright}s heading angle and position. The tests results show our navigation has an accuracy of 0.3 m for position and 0.6° for heading angle, both within the root mean square error (RMSE) criteria. Our analysis shows that the nonlinearity of the gyroscope in the heading rotation axis is the key factor for improving performance in our implementation.",

author = "Xiaolong Zhang and Henri Liikanen and Eelis Peltola and Aref, \{Mohammad M.\} and Jouni Mattila",

note = "JUFOID=87959; European Workshop on Advanced Control and Diagnosis ; Conference date: 21-11-2019 Through 22-11-2019",

year = "2022",

doi = "10.1007/978-3-030-85318-1\_67",

language = "English",

isbn = "978-3-030-85317-4",

series = "Lecture Notes in Control and Information Sciences - Proceedings",

publisher = "Springer",

pages = "1155--1172",

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booktitle = "15th European Workshop on Advanced Control and Diagnosis (ACD 2019)",

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Zhang, X, Liikanen, H, Peltola, E, Aref, MM & Mattila, J 2022, Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. in E Zattoni, S Simani & G Conte (eds), 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) : Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019. Lecture Notes in Control and Information Sciences - Proceedings, Springer, pp. 1155-1172, European Workshop on Advanced Control and Diagnosis, Bologna, Italy, 21/11/19. https://doi.org/10.1007/978-3-030-85318-1_67

Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. / Zhang, Xiaolong; Liikanen, Henri; Peltola, Eelis et al.
15th European Workshop on Advanced Control and Diagnosis (ACD 2019) : Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019. ed. / Elena Zattoni; Silvio Simani; Giuseppe Conte. Springer, 2022. p. 1155-1172 (Lecture Notes in Control and Information Sciences - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry

AU - Zhang, Xiaolong

AU - Liikanen, Henri

AU - Peltola, Eelis

AU - Aref, Mohammad M.

AU - Mattila, Jouni

N1 - JUFOID=87959

PY - 2022

Y1 - 2022

N2 - We introduce a localization algorithm that uses an inertial measurement unit (IMU) and wheel odometry on a four-wheel-drive heavy vehicle for positioning. While wheel odometry alone works in simple cases without slippage, in cases that feature wheel slippage, the velocities measured by the wheel rotation show higher values. In the case of side slippage, the wheel sensors cannot observe the values. Therefore, IMUs are suitable for fusion with wheel odometry to generate real-time feedback. We use an error state Kalman filter (ESKF) to fuse the sensor information from an IMU with wheel odometry, showing results on a slow-manoeuvring vehicle in tests up to five minutes in length. The IMU is an industry-grade micro-electro mechanical system (MEMS) with a gyroscope featuring 6°/h bias in-run stability. We use a real-time kinematic global positioning system (RTK)-GPS as a ground truth reference for the vehicle’s heading angle and position. The tests results show our navigation has an accuracy of 0.3 m for position and 0.6° for heading angle, both within the root mean square error (RMSE) criteria. Our analysis shows that the nonlinearity of the gyroscope in the heading rotation axis is the key factor for improving performance in our implementation.

AB - We introduce a localization algorithm that uses an inertial measurement unit (IMU) and wheel odometry on a four-wheel-drive heavy vehicle for positioning. While wheel odometry alone works in simple cases without slippage, in cases that feature wheel slippage, the velocities measured by the wheel rotation show higher values. In the case of side slippage, the wheel sensors cannot observe the values. Therefore, IMUs are suitable for fusion with wheel odometry to generate real-time feedback. We use an error state Kalman filter (ESKF) to fuse the sensor information from an IMU with wheel odometry, showing results on a slow-manoeuvring vehicle in tests up to five minutes in length. The IMU is an industry-grade micro-electro mechanical system (MEMS) with a gyroscope featuring 6°/h bias in-run stability. We use a real-time kinematic global positioning system (RTK)-GPS as a ground truth reference for the vehicle’s heading angle and position. The tests results show our navigation has an accuracy of 0.3 m for position and 0.6° for heading angle, both within the root mean square error (RMSE) criteria. Our analysis shows that the nonlinearity of the gyroscope in the heading rotation axis is the key factor for improving performance in our implementation.

U2 - 10.1007/978-3-030-85318-1_67

DO - 10.1007/978-3-030-85318-1_67

M3 - Conference contribution

SN - 978-3-030-85317-4

T3 - Lecture Notes in Control and Information Sciences - Proceedings

SP - 1155

EP - 1172

BT - 15th European Workshop on Advanced Control and Diagnosis (ACD 2019)

A2 - Zattoni, Elena

A2 - Simani, Silvio

A2 - Conte, Giuseppe

PB - Springer

T2 - European Workshop on Advanced Control and Diagnosis

Y2 - 21 November 2019 through 22 November 2019

ER -

Zhang X, Liikanen H, Peltola E, Aref MM, Mattila J. Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. In Zattoni E, Simani S, Conte G, editors, 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) : Proceedings of the Workshop Held in Bologna, Italy, on November 21–22, 2019. Springer. 2022. p. 1155-1172. (Lecture Notes in Control and Information Sciences - Proceedings). doi: 10.1007/978-3-030-85318-1_67

Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry

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