We consider the problem of co-designing embodied intelligence as a whole in a structured way, from hardware components such as propulsion systems and sensors to software modules such as control and perception pipelines. We propose a principled approach to formulate and solve complex embodied intelligence co-design problems, leveraging a monotone co-design theory. The methods we propose are intuitive and integrate heterogeneous engineering disciplines, allowing analytical and simulation-based modeling techniques and enabling interdisciplinarity. We illustrate through a case study how, given a set of desired behaviors, our framework is able to compute Pareto efficient solutions for the entire hardware and software stack of a self-driving vehicle.
@article{arxiv.2011.10756,
title = {Co-Design of Embodied Intelligence: A Structured Approach},
author = {Gioele Zardini and Dejan Milojevic and Andrea Censi and Emilio Frazzoli},
journal= {arXiv preprint arXiv:2011.10756},
year = {2021}
}
Comments
8 pages, 9 figures, To appear in the Proceedings of the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems