Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot
This work addresses the problem of efficient multi-modal robot design for applications requiring both aerial and ground mobility, though it is incremental as it builds on existing generative design methods.
The researchers tackled the challenge of designing a robot that integrates aerial and quadrupedal locomotion under tight power and payload constraints by formulating the Mobility Value of Added Mass (MVAM) problem and using generative design to optimize mass allocation. They found that a front-heavy quadrupedal robot achieved a lower Total Cost of Transport (TCOT) and allowed more added mass, which was validated through building and testing the Husky Carbon robot.
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.