by Y. Fan, D. Antonelli, A. Simeone, N. Bao
Abstract
The integration of neurodiverse operators in industry poses interesting challenges highlighting the potential for human-robot collaboration(HRC) to provide the necessary support and assistance to complete manufacturing tasks. This study proposes a reciprocal learning-based framework to support the operator to carry out assembly tasks via collaborative robot (Cobot) assistance. Such framework includes image acquisition and processing, machine learning (ML)-based classification of workpieces and Cobot operational tasks.
An experimental case study is proposed to verify the framework applicability to a number of likely scenarios. Preliminary results show the suitability of HRC systens to effectively aid neurodiverse operators with memory issues in performing assembly tasks correctly, while at the same time improving the operator’s ability to learn the assembly sequence and iteratively improving ML classification accuracy. The potential for intelligent robotics-based increased inclusiveness in manufacturing industry is discussed in terms of benefits to support individuals with cognitive disabilities.
Keywords: Reciprocal learning; Inclusive manufacturing; Human-Robot Collaboration; Neurodiversity
Video presentation
Presenting author
 | Name: Affiliation: Email: | Yuchen Fan Shantou University, China 20ycfan@stu.edu.cn |
