Co-Design of Autonomous Systems: From Hardware Selection to Control Synthesis

TL;DR

This paper presents a formalized approach to co-designing control algorithms and hardware platforms for autonomous systems, enabling Pareto-efficient solutions for complex robotic tasks like search-and-rescue.

Contribution

It introduces a monotone theory-based formalization for co-design problems, integrating control and platform design in a unified framework.

Findings

Formalization of control co-design as monotone feasibility relations

Application to autonomous drone search-and-rescue tasks

Ability to compute Pareto efficient design solutions

Abstract

Designing cyber-physical systems is a complex task which requires insights at multiple abstraction levels. The choices of single components are deeply interconnected and need to be jointly studied. In this work, we consider the problem of co-designing the control algorithm as well as the platform around it. In particular, we leverage a monotone theory of co-design to formalize variations of the LQG control problem as monotone feasibility relations. We then show how this enables the embedding of control co-design problems in the higher level co-design problem of a robotic platform. We illustrate the properties of our formalization by analyzing the co-design of an autonomous drone performing search-and-rescue tasks and show how, given a set of desired robot behaviors, we can compute Pareto efficient design solutions.