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Pixi: Unified Software Development and Distribution for Robotics and AI

Robotics 2025-11-10 v1 Software Engineering

Abstract

The reproducibility crisis in scientific computing constrains robotics research. Existing studies reveal that up to 70% of robotics algorithms cannot be reproduced by independent teams, while many others fail to reach deployment because creating shareable software environments remains prohibitively complex. These challenges stem from fragmented, multi-language, and hardware-software toolchains that lead to dependency hell. We present Pixi, a unified package-management framework that addresses these issues by capturing exact dependency states in project-level lockfiles, ensuring bit-for-bit reproducibility across platforms. Its high-performance SAT solver achieves up to 10x faster dependency resolution than comparable tools, while integration of the conda-forge and PyPI ecosystems removes the need for multiple managers. Adopted in over 5,300 projects since 2023, Pixi reduces setup times from hours to minutes and lowers technical barriers for researchers worldwide. By enabling scalable, reproducible, collaborative research infrastructure, Pixi accelerates progress in robotics and AI.

Keywords

Cite

@article{arxiv.2511.04827,
  title  = {Pixi: Unified Software Development and Distribution for Robotics and AI},
  author = {Tobias Fischer and Wolf Vollprecht and Bas Zalmstra and Ruben Arts and Tim de Jager and Alejandro Fontan and Adam D Hines and Michael Milford and Silvio Traversaro and Daniel Claes and Scarlett Raine},
  journal= {arXiv preprint arXiv:2511.04827},
  year   = {2025}
}

Comments

20 pages, 3 figures, 11 code snippets

R2 v1 2026-07-01T07:25:23.519Z