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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 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 the open‐source software 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.
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Online System Identification and Calibration of Dynamic Models for Autonomous Ground Vehicles
This paper is concerned with system identification and the calibration of parameters of dynamic models used in different robotic platforms. A constant time algorithm has been developed in order to automatically calibrate the parameters of a high-fidelity dynamical model for a robotic platform. The presented method is capable of choosing informative motion segments in order to calibrate model parameters in constant time while also calculating a confidence level on each estimated parameter. Simulations and experiments with a 1/8th scale four wheel drive vehicle are performed to calibrate two of the parameters of test vehicle which demonstrate the accuracy and efficiency of the approach.
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- Award ID(s):
- 1646556
- PAR ID:
- 10078981
- Date Published:
- Journal Name:
- IEEE International Conference on Robotics and Automation (ICRA)
- Page Range / eLocation ID:
- 4933 to 4939
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICRA.2018.8460691
