# SIERRA: A Modular Framework for Research Automation

arXiv: https://arxiv.org/abs/2203.04748 · HTML: https://mlsanity.com/paper/2203.04748/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 13 references that are in the map.
- First posted on arXiv 3 Mar 2022.

## Builds on (most cited first, 5 of 5)

- [The Robotarium: A remotely accessible swarm robotics research testbed](https://mlsanity.com/paper/1609.04730/) (2016)
- [Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10,000 Robot Swarm](https://mlsanity.com/paper/1907.03880/) (2019)
- [Webots.HPC: A Parallel Robotics Simulation Pipeline for Autonomous Vehicles on High Performance Computing](https://mlsanity.com/paper/2108.00485/) (2021)
- [Characterizing The Limits of Linear Modeling of Non-Linear Swarm Behaviors](https://mlsanity.com/paper/2110.12307/) (2021)
- [Improved Swarm Engineering: Aligning Intuition and Analysis](https://mlsanity.com/paper/2012.04144/) (2020)

## Built on by (most cited first, 1 of 1)

- [SIERRA: A Modular Framework for Research Automation and Reproducibility](https://mlsanity.com/paper/2208.07805/) (2022)

## Abstract (arXiv)

Modern intelligent systems researchers employ the scientific method: they form hypotheses about system behavior, and then run experiments using one or more independent variables to test their hypotheses. We present SIERRA, a novel framework structured around that idea for accelerating research developments and improving reproducibility of results. SIERRA makes it easy to quickly specify the independent variable(s) for an experiment, generate experimental inputs, automatically run the experiment, and process the results to generate deliverables such as graphs and videos. SIERRA provides reproducible automation independent of the execution environment (HPC hardware, real robots, etc.) and targeted platform (arbitrary simulator or real robots), enabling exact experiment replication (up to the limit of the execution environment and platform). It employs a deeply modular approach that allows easy customization and extension of automation for the needs of individual researchers, thereby eliminating manual experiment configuration and result processing via throw-away scripts.