Date of Award

Summer 2022

Document Type

Thesis - Open Access

Degree Name

Master of Aerospace Engineering


College of Engineering

Committee Chair

Dr. Mandar Kulkarni

First Committee Member

Dr. Ali Yeilaghi Tamijani

Second Committee Member

Dr. Alberto Mello

Third Committee Member

Dr. Sirish Namilae


Rovers have been launched into space for exploration of the Moon and Mars to collect samples of rock and soil. To continue the explorations, the rovers need to have reliable wheels to drive around. However, due to the soil being soft, the wheels on the rover start to lose traction and the wheels sink while driving to various locations. Previous work in this field has been done experimentally or with the use of simulations. Only a few references report the effect of uncertainties in grouser simulation on the traction efficiency. The objective of this work was to (a) Understand the effect of uncertainties on wheel traction efficiency, and (b) Design a rover wheel, consider those uncertainties, and then compare results with deterministic optimization. The results are categorized into three different sections. The first section shows the result of a closed-form equation for rover traction efficiency. A closed-form equation was obtained using three different formulas from previous work. The second section provides results on a reliability analysis to understand the effects of uncertainty on traction efficiency. The uncertainty variables chosen were the empiric soil parameter, , the weight of the wheel, w, and the width of the wheel, b. The third section has a result of using the reliability-based design for the wheel considering those uncertainties, in which the design parameters are the normalized height of the grousers, , the width of the wheel, b, the radius of the wheel, r, and finally the weight of the wheel, w. In the reliability-based optimization there are two variables that are considered uncertain which are not the design parameters, the soil parameter and torque. In the design parameters, the radius of the wheel is considered uncertain. Once the optimized values are obtained, they are compared to the deterministic optimization. As a result, optimized design variables were obtained.