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Journal of Computational and Nonlinear Dynamics | Volume 10 | Issue 5 | research-article
Research Papers

Experimental Validation of a Volumetric Planetary Rover Wheel/Soil Interaction Model

[+] Author and Article Information
Willem Petersen

Department of Systems Design Engineering,
University of Waterloo,
Waterloo, Ontario N2L 3G1, Canada
e-mail: wpeterse@uwaterloo.ca

John McPhee

Department of Systems Design Engineering,
University of Waterloo,
Waterloo, Ontario N2L 3G1, Canada
e-mail: mcphee@uwaterloo.ca

The boundary effects have been neglected.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received June 19, 2013; final manuscript received November 25, 2014; published online April 2, 2015. Assoc. Editor: Parviz Nikravesh.

J. Comput. Nonlinear Dynam 10(5), 051001 (Sep 01, 2015) (12 pages) Paper No: CND-13-1146; doi: 10.1115/1.4029257 History: Received June 19, 2013; Revised November 25, 2014; Online April 02, 2015
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For the multibody simulation of planetary rover operations, a wheel–soil contact model is necessary to represent the forces and moments between the tire and the soft soil. A novel nonlinear contact modeling approach based on the properties of the hypervolume of interpenetration is validated in this paper. This normal contact force model is based on the Winkler foundation model with nonlinear spring properties. To fully define the proposed normal contact force model for this application, seven parameters are required. Besides the geometry parameters that can be easily measured, three soil parameters representing the hyperelastic and plastic properties of the soil have to be identified. Since it is very difficult to directly measure the latter set of soil parameters, they are identified by comparing computer simulations with experimental results of drawbar pull tests performed under different slip conditions on the Juno rover of the Canadian Space Agency (CSA). A multibody dynamics model of the Juno rover including the new wheel/soil interaction model was developed and simulated in maplesim. To identify the wheel/soil contact model parameters, the cost function of the model residuals of the kinematic data is minimized. The volumetric contact model is then tested by using the identified contact model parameters in a forward dynamics simulation of the rover on an irregular three-dimensional terrain and compared against experiments.
Copyright © 2015 by ASME
Topics: Simulation , Soil , Wheels
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References

Figures

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Fig. 1

Volumetric wheel/soil model schematic

+Volumetric wheel/soil model schematic
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Volumetric wheel/soil model schematic
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Fig. 2

Juno rover (approx. dimensions 1.5 × 1.5 × 0.6 m)

+Juno rover (approx. dimensions 1.5 × 1.5 × 0.6 m)
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Juno rover (approx. dimensions 1.5 × 1.5 × 0.6 m)
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Fig. 3

Juno rover model as implemented in maplesim

+Juno rover model as implemented in maplesim
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Juno rover model as implemented in maplesim
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Fig. 4

Optimization inputs from experimental data of the first drawbar pull test

+Optimization inputs from experimental data of the first drawbar pull test
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Optimization inputs from experimental data of the first drawbar pull test
Grahic Jump Location
Fig. 5

Optimization objectives from experimental data of the first drawbar pull test

+Optimization objectives from experimental data of the first drawbar pull test
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Optimization objectives from experimental data of the first drawbar pull test
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Fig. 6

Optimization inputs from experimental data of the second drawbar pull test

+Optimization inputs from experimental data of the second drawbar pull test
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Optimization inputs from experimental data of the second drawbar pull test
Grahic Jump Location
Fig. 7

Optimization objectives from experimental data of the second drawbar pull test

+Optimization objectives from experimental data of the second drawbar pull test
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Optimization objectives from experimental data of the second drawbar pull test
Grahic Jump Location
Fig. 8

Optimization inputs from experimental data of the third drawbar pull test

+Optimization inputs from experimental data of the third drawbar pull test
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Optimization inputs from experimental data of the third drawbar pull test
Grahic Jump Location
Fig. 9

Optimization objectives from experimental data of the third drawbar pull test

+Optimization objectives from experimental data of the third drawbar pull test
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Optimization objectives from experimental data of the third drawbar pull test
Grahic Jump Location
Fig. 10

Comparison of the identified model parameters. For the curve fit, the characteristic nonlinear model provided by the contact model was used.

+Comparison of the identified model parameters. For the curve fit, the characteristic nonlinear model provided by the contact model was used.
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Comparison of the identified model parameters. For the curve fit, the characteristic nonlinear model provided by the contact model was used.
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Fig. 11

Raw LIDAR scan data

+Raw LIDAR scan data
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Raw LIDAR scan data
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Fig. 12

Scanned 3D terrain of experiment

+Scanned 3D terrain of experiment
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Scanned 3D terrain of experiment
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Fig. 13

Comparison of longitudinal dynamics

+Comparison of longitudinal dynamics
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Comparison of longitudinal dynamics
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Fig. 14

Comparison of wheel spin

+Comparison of wheel spin
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Comparison of wheel spin
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Fig. 15

Comparison of drive torques (controlling wheel spin)

+Comparison of drive torques (controlling wheel spin)
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Comparison of drive torques (controlling wheel spin)
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Fig. 16

Longitudinal speed of chassis and curve-fit for simulation

+Longitudinal speed of chassis and curve-fit for simulation
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Longitudinal speed of chassis and curve-fit for simulation
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Fig. 17

Comparison of longitudinal speed of chassis and prism

+Comparison of longitudinal speed of chassis and prism
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Comparison of longitudinal speed of chassis and prism
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Fig. 18

Comparison of drive torques (controlling forward speed)

+Comparison of drive torques (controlling forward speed)
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Comparison of drive torques (controlling forward speed)

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