# DULA: A Differentiable Ergonomics Model for Postural Optimization in Physical HRI

arXiv: https://arxiv.org/abs/2107.06875 · HTML: https://mlsanity.com/paper/2107.06875/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 24 references that are in the map.
- First posted on arXiv 14 Jul 2021.

## Builds on (most cited first, 4 of 4)

- [Pose Trainer: Correcting Exercise Posture using Pose Estimation](https://mlsanity.com/paper/2006.11718/) (2020)
- [Real-time Robot-assisted Ergonomics](https://mlsanity.com/paper/1805.06270/) (2018)
- [Data-Driven Approach to Simulating Realistic Human Joint Constraints](https://mlsanity.com/paper/1709.08685/) (2017)
- [Planning for Muscular and Peripersonal-Space Comfort during Human-Robot Forceful Collaboration](https://mlsanity.com/paper/1807.11323/) (2018)

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

- [Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization](https://mlsanity.com/paper/2108.05971/) (2021)

## Abstract (arXiv)

Ergonomics and human comfort are essential concerns in physical human-robot interaction applications. Defining an accurate and easy-to-use ergonomic assessment model stands as an important step in providing feedback for postural correction to improve operator health and comfort. In order to enable efficient computation, previously proposed automated ergonomic assessment and correction tools make approximations or simplifications to gold-standard assessment tools used by ergonomists in practice. In order to retain assessment quality, while improving computational considerations, we introduce DULA, a differentiable and continuous ergonomics model learned to replicate the popular and scientifically validated RULA assessment. We show that DULA provides assessment comparable to RULA while providing computational benefits. We highlight DULA's strength in a demonstration of gradient-based postural optimization for a simulated teleoperation task.