Improving Human-Robot Physical Interaction Comfort in Material Handling Tasks Using a Smart Platform

Kochubey Dmitry ()
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Kochubey Dmitry: Technical University of Liberec, Faculty of Mechanical Engineering, Institute of Mechatronics and Computer Engineering, Studentská 1402/2, 461 17, Liberec 1, Czech Republic

ACC Journal, 2023, vol. 29, issue 1, 23-33

Abstract: The use of mobile platforms can help employees automate manual processes and streamline operations to save time and perform their tasks safely and accurately. A power-assisted vehicle to move weight around the place – solution: inexpensive, easy to apply, reliable, safe. It can adjust to various tasks, operators’ gait, loads up to 500 kg. It is a relatively inexpensive, easy-to-apply, reliable, and safe solution for moving weight. The motivation of the study is to increase efficiency and reduce physical strain on the operator in material handling tasks and to promote the implementation of this smart platform. Artificial intelligence learning methods are applied to adapt to individual operator’s experience, resulting in a personalized and more comfortable interaction with the help of Q-learning algorithm with 256 learning outcomes in adjusting controller settings: damping, mass, stiffness.

Keywords: Q-learning algorithms; Smart platform; AI; HRI; Material handling tasks; Human comfort criteria (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:accjnl:v:29:y:2023:i:1:p:23-33:n:1002

DOI: 10.15240/tul-004-2023-1-002

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