MARVIN: Multimodally Advantaged Robotic Vehicle for Improved Navigation

Abstract

Hybrid robots leverage the advantages of multiple types of locomotion. More specifically, wheel-legged hybrid robots aim to capture the speed, stability, and power efficiency of wheeled robots as well as the ability to traverse robust natural terrain that legged robots provide. Effective hybrid designs are able to capitalize on both sets of advantages without compromising the overall effectiveness of the machine. Here, we present a design and implementation of MARVIN, a wheel-legged hybrid robot that emphasizes three key features: a quick transition mechanism, a well-defined wheel and leg mode, and the capacity for flexible control through continuously vari-able leg length. We demonstrate how the two clearly defined modes of legs/wheels in MARVIN capitalize on their respective advantages. Furthermore, in realizing the tradeoff between modes specific to this robot, we derive a hybrid path-planning algorithm using an empirically driven cost function, which we found by collecting data in real-terrain experiments. We discuss our mechanical, electronic, and software design approaches in building a prototype of the proposed design. We also review our experimental methods. Lastly, we point out lessons learned from the operation of our prototype robot, identifying directions for future upgrades.