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Estimating friction coefficient using generative modelling

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conference contribution
posted on 2023-05-25, 13:25 authored by Mohammad OtoofiMohammad Otoofi, William JB Midgley, Leo Laine, Leon Henderson, Laura JusthamLaura Justham, James FlemingJames Fleming
It is common to utilise dynamic models to measure the tyre-road friction in real-time. Alternatively, predictive approaches estimate the tyre-road friction by identifying the environmental factors affecting it. This work aims to formulate the problem of friction estimation as a visual perceptual learning task. The problem is broken down into detecting surface characteristics by applying semantic segmentation and using the extracted features to predict the frictional force. This work for the first time formulates the friction estimation problem as a regression from the latent space of a semantic segmentation model. The preliminary results indicate that this approach can estimate frictional force.

Funding

Volvo Trucks

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

2023 IEEE International Conference on Mechatronics (ICM)

Source

2023 IEEE International Conference on Mechatronics (ICM)

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2023-04-17

Copyright date

2023

ISBN

9781665466615

Language

  • en

Location

Loughborough, United Kingdom

Event dates

15th March 2023 - 17th March 2023

Depositor

Dr James Fleming. Deposit date: 23 May 2023

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