# 5295 / Model-Based Online Optimal Control For Vehicles In Reduced Gravity. ## Authors Chaitanya Sonalkar, Adwait Verulkar, and Corina Sandu {% hint style="info" %} Paper presented at ISTVS 2024 | 21st International and 12th Asia-Pacific Regional Conference of the ISTVS\ Keywords: Off-road mobility; Vehicle dynamics; Extraterrestrial rovers; Optimal control; Terramechanics\ {% endhint %} ## Abstract There has been an interest in the exploration of planetary bodies for more than half a century. Scientific research has been focused on understanding the origins of life, potential for habitability in extraterrestrial environments, and discovery of rare minerals and energy sources. Extraterrestrial rovers have been used previously by space agencies for the exploration of Lunar and Martian surfaces. Reduced gravity on such surfaces influences the performance and mobility of extraterrestrial vehicles. Gravity can change how the soil behaves under the wheel as well as the traction force and sinkage developed by the wheel. The sinkage rate and depth of a wheel and motion resistance are also impacted by gravity. As the rovers are operated by interplanetary telemetry, autonomous real-time control is employed in these systems due to communication delays. Optimal online control with a high-fidelity terramechanics model may not be feasible and it necessitates the development of simplified models which consider the effect of reduced gravity on dynamics of a vehicle. The goal of this work is to study the effect of reduced gravity on Lunar terrain and its effect on vehicle performance of rovers through analytical modeling of tire-terrain interaction. We have developed an optimal control algorithms to improve vehicle stability and trajectory tracking performance in standard maneuvers. The simplified terrain models can also be extended for hardware-in-loop simulations. *** Full paper purchase: \ ISTVS members receive three complimentary papers per year: --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://2024.istvs.org/submissions/papers/5295.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.