Calibration of an expeditious terramechanics model using a
higher-fidelity model, Bayesian inference, and a virtual bevameter test
Abstract
The soil contact model (SCM) is widely used in practice for off-road
wheeled vehicle mobility studies when simulation speed is important and
highly accurate results are not a main concern. In practice, the SCM
parameters are obtained via a bevameter test, which requires a complex
apparatus and experimental procedure. Here, we advance the idea of
running a virtual bevameter test using a high-fidelity terramechanics
simulation. The latter employs the “continuous representation model”
(CRM), which regards the deformable terrain as an elasto-plastic
continuum that is spatially discretized using the smoothed particle
hydrodynamics (SPH) method. The approach embraced is as follows: a
virtual bevameter test is run in simulation using CRM terrain to
generate “ground truth” data; in a Bayesian framework, this data is
subsequently used to calibrate the SCM terrain. We show that (i) the
resulting SCM terrain, while leading to fast terramechanics simulations,
serves as a good proxy for the more complex CRM terrain; and (ii) the
SCM-over-CRM simulation speedup is roughly one order of magnitude. These
conclusions are reached in conjunction with two tests: a single wheel
test, and a full rover simulation. The SCM and CRM simulations are run
in an open-source software called Chrono. The calibration is performed
using PyMC, which is a Python package that interactively communicates
with Chrono to calibrate SCM. The models and scripts used in this
contribution are available as open source for unfettered use and
distribution in a public repository.