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Experimental Evaluation of Rover Mobility Prediction Methods using Single Wheel Experiments

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Experimental Evaluation of Rover Mobility Prediction Methods using Single Wheel Experiments

Demishkevich, Alexander (2025) Experimental Evaluation of Rover Mobility Prediction Methods using Single Wheel Experiments. Masters thesis, Concordia University.

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Abstract

Multiple lunar exploration activities from around the world are driving the development of small skid-steer rovers for Moon missions. Single wheel experiments are commonly done to approximate the mobility of a rover design. This research aims to evaluate the limitations and accuracy of simple approximation models. In this work, single-wheel and full rover laboratory experimentation methods are described for systematic comparison of wheel designs in point turns and slope climbing. The effects of lunar gravity are accounted for using Granular Scaling Laws and GRC-1 lunar simulant in all experiments. Single wheel experiments are paired with simple theoretical models to predict full rover performance. The accuracy of the predictions is confirmed using scaled tests with a full rover. Slanted grousers are shown to be compared favorably against V-offset grousers for point turns, achieving successful point turning with approximately 30\% slip in single-wheel and full rover experiments. This also showed that single wheel experiments can accurately predict full rover performance in point turns. On the other hand, slope climbing predictions had a substantial amount of errors. In part, this error was found to be explained by the diameter/width value of the wheel, with larger values being associated to a higher prediction error. To reduce prediction error a correction factor can be approximated by applying a correction factor to rigid wheel test data.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Demishkevich, Alexander
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:20 January 2025
Thesis Supervisor(s):Skonieczny, Krzysztof
ID Code:995136
Deposited By: Alexander Demishkevich
Deposited On:17 Jun 2025 17:10
Last Modified:17 Jun 2025 17:10
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