# A Framework for Closed-Loop Robotic Assembly, Alignment and Self-Recovery of Precision Optical Systems

arXiv: https://arxiv.org/abs/2603.21496 · HTML: https://mlsanity.com/paper/2603.21496/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 24 references that are in the map.
- First posted on arXiv 23 Mar 2026.

## Builds on (most cited first, 8 of 8)

- [ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization](https://mlsanity.com/paper/2401.06949/) (2024)
- [Interferobot: aligning an optical interferometer by a reinforcement learning agent](https://mlsanity.com/paper/2006.02252/) (2020)
- [RoboCulture: A Robotics Platform for Automated Biological Experimentation](https://mlsanity.com/paper/2505.14941/) (2025)
- [Active Alignments of Lens Systems with Reinforcement Learning](https://mlsanity.com/paper/2503.02075/) (2025)
- [Aligning an optical interferometer with beam divergence control and continuous action space](https://mlsanity.com/paper/2107.04457/) (2021)
- [Model-free reinforcement learning with noisy actions for automated experimental control in optics](https://mlsanity.com/paper/2405.15421/) (2024)
- [AI-Driven Robotics for Optics](https://mlsanity.com/paper/2505.17985/) (2025)
- [Action-Attentive Deep Reinforcement Learning for Autonomous Alignment of Beamlines](https://mlsanity.com/paper/2411.12183/) (2024)

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

- [Vision-Language Agents for Active Perception in Optics Laboratories](https://mlsanity.com/paper/2609.32918/) (2026)

## Abstract (arXiv)

Robotic automation has transformed scientific workflows in domains such as chemistry and materials science, yet free-space optics, which is a high precision domain, remains largely manual. Optical systems impose strict spatial and angular tolerances, and their performance is governed by tightly coupled physical parameters, making generalizable automation particularly challenging. In this work, we present a robotics framework for the autonomous construction, alignment, and maintenance of precision optical systems. Our approach integrates hierarchical computer vision systems, optimization routines, and custom-built tools to achieve this functionality. As a representative demonstration, we perform the fully autonomous construction of a tabletop laser cavity from randomly distributed components. The system performs several tasks such as laser beam centering, spatial alignment of multiple beams, resonator alignment, laser mode selection, and self-recovery from induced misalignment and disturbances. By achieving closed-loop autonomy for highly sensitive optical systems, this work establishes a foundation for autonomous optical experiments for applications across technical domains.