# Robot Co-design: Beyond the Monotone Case

## TL;DR

This paper introduces a binary optimization approach for robot co-design, enabling automatic selection of modules to optimize performance and cost, demonstrated on drone racing and multi-robot systems.

## Contribution

It presents a generalized binary optimization formulation for robot co-design that surpasses previous models and efficiently solves large problems with minimal human input.

## Key findings

- Can solve large co-design problems in seconds
- Effective in designing autonomous drone racing platforms
- Applicable to multi-robot system design

## Abstract

Recent advances in 3D printing and manufacturing of miniaturized robotic hardware and computing are paving the way to build inexpensive and disposable robots. This will have a large impact on several applications including scientific discovery (e.g., hurricane monitoring), search-and-rescue (e.g., operation in confined spaces), and entertainment (e.g., nano drones). The need for inexpensive and task-specific robots clashes with the current practice, where human experts are in charge of designing hardware and software aspects of the robotic platform. This makes the robot design process expensive and time-consuming, and ultimately unsuitable for small-volumes low-cost applications. This paper considers the computational robot co-design problem, which aims to create an automatic algorithm that selects the best robotic modules (sensing, actuation, computing) in order to maximize the performance on a task, while satisfying given specifications (e.g., maximum cost of the resulting design). We propose a binary optimization formulation of the co-design problem and show that such formulation generalizes previous work based on strong modeling assumptions. We show that the proposed formulation can solve relatively large co-design problems in seconds and with minimal human intervention. We demonstrate the proposed approach in two applications: the co-design of an autonomous drone racing platform and the co-design of a multi-robot system.