Exploring Benchmarks for Self-Driving Labs using Color Matching

TL;DR

This paper presents a robotic system for autonomous color matching in Self Driving Labs, demonstrating a flexible, portable, and automated approach to experimental workflows that can serve as a benchmark for autonomous scientific discovery.

Contribution

It introduces a robotic color matching solution that integrates platform portability, alternative optimization methods, and automated result publication for SDL benchmarking.

Findings

Fully autonomous execution of color matching protocol

Platform-agnostic robotic implementation

Automated data publication for analysis

Abstract

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.