Empirical study for human engagement in collaborative robot programming
Joao Paulo Jacomini Prioli, Shengyu Liu, Yinfeng Shen, Van Thong Huynh, Jeremy L. Rickli, Hyung-Jeong Yang, Soo-Hyung Kim, Kyoung‐Yun Kim
- 发表年份
- 2022
- 引用次数
- 5
摘要
The need for flexible production has turned manufacturing’s attention to integrate fast and uncomplicated solutions. Collaborative robots (cobots) have been considered the most impactful technology due to their versatility and human-robot interaction feature. Its implementation requires expertise in both process and cobot programming. Consequently, demand for effective programming training has increased over the past years. This paper, then, aims to design and explore a smart cobot programming system and conduct an empirical study to understand human engagement and programming performance. A repertory grid is employed based on cobot experts to understand different cobot programming approaches. Meaningful insights were considered to design and implement a smart programming system configuration. Then, an empirical programming study was performed considering cobot expertise and human engagement. Results demonstrated similarities and disparities in data collected, which was inferred to indicate differences in cobot programming behavior. Finally, the work identifies and discusses patterns to differentiate programmer expertise levels and behaviors.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002