日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2108.05971

Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization

Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization

シェア:XThreadsFacebookLINEはてブBluesky

著者: Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

分類: cs.RO, cs.AI, cs.HC, cs.LG

原文アブストラクト

Ergonomics and human comfort are essential concerns in physical human-robot interaction. Common practical methods in the area either fail in estimating the correct posture due to occlusion or suffer from inaccurate ergonomics models in performing postural optimization. We propose a novel alternative framework for posture estimation, assessment, and optimization for ergonomically intelligent physical human-robot interaction. We show that we can estimate human posture solely from the trajectory of the interacting robot with median deviation of 5 deg from motion capture. We propose DULA, a differentiable ergonomics assessment tool with 99.73% accuracy comparing to RULA. We use DULA in postural optimization for physical human-robot interaction tasks such as co-manipulation and teleoperation. We evaluate our framework through human and simulation experiments.