Towards Autonomous Ergonomic Upper-limb Exoskeletons: A Computational Approach for Planning Human-like Path
Towards Autonomous Ergonomic Upper-limb Exoskeletons: A Computational Approach for Planning Human-like Path
复制标题
走向自主人体工学上肢外骨骼：规划类人路径的计算方法
DOI：
10.1016/j.robot.2021.103843
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发表时间：
2021
影响因子：
4.3
通讯作者：
Robson N
中科院分区：
文献类型：
--
作者：
Soltani-Zarrin, R;Zeiaee A;Langari R;Buchanan J;Robson N
计算路径规划方法可以实现自主康复和辅助外骨骼的开发。为这种可穿戴系统使用类似人类的参考行为可以确保安全，有效和直观的人机交互。这是非常重要的，因为交互的质量和人体工程学的考虑对技术的可用性和用户的接受度有很大的影响。本文提出了一种新的框架，用于在肩肘级别生成可穿戴外骨骼的类人路径。所介绍的方法是一个两阶段的过程，其中类人的参考路径在人的手臂的配置空间中进行规划，然后进行分析变换，直接将导出的路径映射到外骨骼的配置空间。所提出的解析映射是系统的运动学参数的函数，并且可以适用于其他上肢外骨骼。作为一个案例研究，所提出的方法用于生成类人的参考运动的六度自由度外骨骼支持肩胛肱骨节律，盂肱关节旋转，和肘关节屈曲/伸展。首先，它表明，达到与日常生活活动相关的运动可以预测在人体关节空间的高精度。通过分析从健康受试者收集的实验数据证明了这一点。随后，通过运动学分析验证，所生成的路径到外骨骼配置空间的变换不会改变它们在任务空间中的空间轮廓。
Computational path planning approaches can enable development of autonomous rehabilitation and assistive exoskeletons. Using a human-like reference behavior for such wearable systems can ensure safe, effective, and intuitive human–robot interaction. This is of significant importance since the quality of interaction and ergonomic considerations have a substantial effect on technology usability and acceptance by the users. This paper proposes a novel framework for generating human-like paths for wearable exoskeletons in the shoulder-elbow level. The introduced method is a two-stage process where a human-like reference path is planned in the configuration space of the human arm, followed by an analytical transformation that directly maps the derived path to the configuration space of the exoskeleton. The analytical mapping presented is a function of the kinematic parameters of the system and can be adapted for other upper-limb exoskeletons. As a case study, the proposed method is used for generating human-like reference motions for a six-degree-of-freedom exoskeleton supporting scapulohumeral rhythm, glenohumeral rotations, and elbow flexion/extension. Firstly, it is shown that reaching motions associated with activities of daily living can be predicted with high accuracy in the human joint space. This is demonstrated by analyzing the experimental data collected from healthy subjects. Subsequently, it is verified through kinematic analysis that the transformation of generated paths to the exoskeleton configuration space does not alter their spatial profile in the task space.