A computational tool for conceptual design and optimization of planetary rovers

Abstract

The design process of a Mars rover is driven by multiple design constraints, namely overall mass, power consumption and volume (dimensions). Various systems, such as mobility, manipulation, handling, power, thermal, communication, navigation, avionics and science instruments, together make a complete rover vehicle and they should function collectively to perform a given task. Each of the subsystems can be thought of as modular building blocks that are integrated together to form a fully functional rover vehicle. When approaching the design of such a vehicle, the designer should take into account of cross design dependencies existent between different subsystems and technology limitations. Performing any particular task, would lead to many design possibilities. Choosing the final design from many feasible solutions is arguably a daunting task. In order to make this process simple and convenient, as well as to understand the design non-linearity existing in this solution space, the authors have employed a systems engineering approach to develop a tool comprising subsystem models. The subsystem models comprise parametric and physics-based models. For designing suitable user-defined objectives, these models when integrated with Genetic Algorithm forms an effective tool to support design trade-offs during the conceptual design process. This integrated modeling and optimization approach is thought to be efficient in identifying rover system concepts.

Keywords

• mass models
• power models
• environmental models
• design variables
• genetic algorithm
• minimal mass
• maximal science returns
• mobility subsystem
• power subsystem