Neural network enhanced off-road skid-steer vehicle modeling with an application to path planning

This thesis discusses the development and validation of 2D and 3D dynamic skid-steer vehicle models for the purpose of enabling or facilitating the future development of control, path planning, and localization algorithms off-road. The ideal dynamic model is fast, accurate, general, adaptive, and 3D. The work presented in this thesis tries to approach this ideal with different models. First, a very simple linear 2D vehicle model was trained from data as a benchmark. Following this, a more complex 2D neural network model was developed. Next, a 3D floating base dynamic vehicle model was created. This was integrated with the Bekker tire-soil model which was approximated with a neural network and used to realistically simulate terrain. Auto differentiation was leveraged to create a fully differentiable 3D simulation which enabled optimization techniques. Gradient descent was used to select soil parameters that maximized 3D model accuracy and achieved offline model adaption to unknown soil types. Finally, experiments were performed to train the 3D vehicle model as a physics based neural ODE. All vehicle models were trained and evaluated with an external data set. To demonstrate the usefulness of the 3D model, a Rapid Random Trees (RRT) algorithm was implemented in simulation to search for valid paths across a 3D terrain.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Yurkanin, Justin

Contributors dc:contributor

• Norris, William R
• Ramos, Joao

• Off-road
• neural ODE
• dynamics
• Autonomous

Statement dc:rights

• Copyright 2022 Justin Yurkanin

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/115870

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F115870