论文标题
Dula和Deba：符合人体工程学智能PHRI的姿势评估和优化的可区分人体工程学风险模型
DULA and DEBA: Differentiable Ergonomic Risk Models for Postural Assessment and Optimization in Ergonomically Intelligent pHRI
论文作者
论文摘要
人体工程学和人类的舒适性是物理人类机器人互动应用中的重要问题。定义准确且易于使用的符合人体工程学评估模型是为姿势校正提供反馈以改善操作员健康和舒适的重要一步。该地区的常见实际方法在执行姿势优化时遭受不准确的人体工程学模型。为了保留评估质量，同时改善了计算考虑因素，我们提出了一个新颖的姿势评估框架，并优化了人体工程学上智能的物理人类机器人相互作用。我们介绍了Dula和Deba，可区分和连续的人体工程学模型学会了以超过99％的精度复制受欢迎和科学验证的Reba评估。我们表明，Dula和Deba提供的评估与Rula和RebA相当，同时在用于姿势优化时提供了计算益处。我们通过人类和仿真实验评估我们的框架。我们强调了Dula和Deba的强度，以展示对模拟PHRI任务的姿势优化。
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.
