Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot

TL;DR

This paper presents a generative design approach for a morpho-functional robot that integrates aerial and quadrupedal locomotion, optimizing mass distribution to improve energy efficiency within tight power and payload constraints.

Contribution

It introduces the MVAM problem and uses an evolutionary generative design method to optimize robot morphology for minimal energy cost, demonstrating a novel integrated design approach.

Findings

Front-heavy design reduces total cost of transport.

Generative design effectively explores morphology options.

Optimized mass distribution improves energy efficiency.

Abstract

We report the design of a morpho-functional robot called Husky Carbon. Our goal is to integrate two forms of mobility, aerial and quadrupedal-legged locomotion, within a single platform. There are prohibitive design restrictions such as tight power budget and payload, which can particularly become important in aerial flights. To address these challenges, we pose a problem called the Mobility Value of Added Mass (MVAM) problem. In the MVAM problem, we attempt to allocate mass in our designs such that the energetic performance is affected the least. To solve the MVAM problem, we adopted a generative design approach using Grasshopper's evolutionary solver to synthesize a parametric design space for Husky. Then, this space was searched for the morphologies that could yield a minimized Total Cost Of Transport (TCOT) and payload. This approach revealed that a front-heavy quadrupedal robot can achieve a lower TCOT while retaining larger margins on allowable added mass to its design. Based on this framework Husky was built and tested as a front-heavy robot.