Interactive Lab Notebooks for Robotics Researchers

TL;DR

This paper explores how interactive notebooks can be adapted for robotics research to improve data management, reproducibility, and workflow efficiency, addressing current limitations in tool compatibility and record-keeping practices.

Contribution

It proposes extending interactive notebooks with features tailored for robotics researchers, enhancing experimental data organization and reproducibility.

Findings

Robotics researchers rely on incompatible tools for data management.

Interactive notebooks can be adapted to support comprehensive data entry.

Enhanced notebooks improve reproducibility and workflow in robotics research.

Abstract

Interactive notebooks, such as Jupyter, have revolutionized the field of data science by providing an integrated environment for data, code, and documentation. However, their adoption by robotics researchers and model developers has been limited. This study investigates the logging and record-keeping practices of robotics researchers, drawing parallels to the pre-interactive notebook era of data science. Through interviews with robotics researchers, we identified the reliance on diverse and often incompatible tools for managing experimental data, leading to challenges in reproducibility and data traceability. Our findings reveal that robotics researchers can benefit from a specialized version of interactive notebooks that supports comprehensive data entry, continuous context capture, and agile data staging. We propose extending interactive notebooks to better serve the needs of robotics researchers by integrating features akin to traditional lab notebooks. This adaptation aims to enhance the organization, analysis, and reproducibility of experimental data in robotics, fostering a more streamlined and efficient research workflow.