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. Common practical methods in
the area suffer from inaccurate ergonomics models in performing postural
optimization. In order to retain assessment quality, while improving
computational considerations, we propose a novel framework for postural
assessment and optimization for ergonomically intelligent physical human-robot
interaction. We introduce DULA and DEBA, differentiable and continuous
ergonomics models learned to replicate the popular and scientifically validated
RULA and REBA assessments with more than 99% accuracy. We show that DULA and
DEBA provide assessment comparable to RULA and REBA while providing
computational benefits when being used in postural optimization. We evaluate
our framework through human and simulation experiments. We highlight DULA and
DEBA's strength in a demonstration of postural optimization for a simulated
pHRI task.

提出了一种基于 DULA 和 DEBA 的人机相互作用姿势评估和优化框架，用于改善人机相互作用中的人体工效学和人体舒适性问题。