Optimization of Small Unmanned Ground Vehicle Design using Reconfigurability, Mobility, and Complexity

Abstract

Unmanned ground vehicles are being deployed in increasingly diverse and complex environments. With modern developments in sensing and planning, the field of ground vehicle mobility presents rich possibilities for mechanical innovations that may be especially relevant for unmanned systems. In particular, reconfigurability may enable vehicles to traverse a wider set of terrains with greater efficiency by allowing them the benefits of multiple configurations. However, reconfigurability is not without its costs including increased size, weight, cost, and complexity. In this work, we present a method for evaluating the positive and negative impacts of reconfigurability to enable the optimization of unmanned vehicle design. We start with the formation of definitions and metrics for reconfigurability, mobility, and complexity, drawing from a wide range of robotic applications. Next, we analyze the combination and optimization of these functions to find ideal physical parameters for a given objective. After that, we delve into the application side of this topic with a case study in reconfigurable vehicles and the design of a novel manually reconfigurable tracked vehicle. Finally, we evaluate this vehicle and validate the optimization method experimentally and through mission scenarios.