文章基本信息

标题：Mechanical and Control Design of an Industrial Exoskeleton for Advanced Human Empowering in Heavy Parts Manipulation Tasks
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作者：Alessandro Mauri ; Jacopo Lettori ; Giovanni Fusi 等
期刊名称：Robotics
电子版ISSN：2218-6581
出版年度：2019
卷号：8
期号：3
页码：65-85
DOI：10.3390/robotics8030065
出版社：MDPI Publishing
摘要：Exoskeleton robots are a rising technology in industrial contexts to assist humans in onerous applications. Mechanical and control design solutions are intensively investigated to achieve a high performance human-robot collaboration (e.g., transparency, ergonomics, safety, etc.). However, the most of the investigated solutions involve high-cost hardware, complex design solutions and standard actuation. Moreover, state-of-the-art empowering controllers do not allow for online assistance regulation and do not embed advanced safety rules. In the presented work, an industrial exoskeleton with high payload ratio for lifting and transportation of heavy parts is proposed. A low-cost mechanical design solution is described, exploiting compliant actuation at the shoulder joint to increase safety in human-robot cooperation. A hierarchic model-based controller with embedded safety rules is then proposed (including the modeling of the compliant actuator) to actively assist the human while executing the task. An inner optimal controller is proposed for trajectory tracking, while an outer safety-based fuzzy logic controller is proposed to online deform the task trajectory on the basis of the human’s intention of motion. A gain scheduler is also designed to calculate the inner optimal control gains on the basis of the performed trajectory. Simulations have been performed in order to validate the performance of the proposed device, showing promising results. The prototype is under realization.
关键词：industrial exoskeleton design; industrial exoskeleton control; human-robot collaboration; optimal control; empowering fuzzy control industrial exoskeleton design ; industrial exoskeleton control ; human-robot collaboration ; optimal control ; empowering fuzzy control