Human-Robot Collaboration: Cognitive and Affective Human Factors In-the-Loop

In collaboration with Dr Duha Ali (Industrial and Manufacturing Engineering Department) and Dr Rafael Guerra, (Orfalea College of Business), we are developing next-generation approaches to human-robot collaboration. A collaborative robot (cobot) is intended for direct human-robot interaction within a shared space or where humans and robots are close. The Cobot is responsible for repetitive, menial tasks, while a human worker completes more complex and thought-intensive tasks. Human-robot collaboration and communication are critical challenges that must be addressed for trust and safety. Affect in a human influences cognitive processes like memory and attention, and Cognition might trigger affective behaviors. Affective states and Cognitive factors are critical in the human decision-making process. While cooperation and communication could come naturally to humans, among others, due to our capacity to identify other humans’ affective and cognitive states, this capability is missing in Human-Robot interaction.

We aim to:

  1. developing collaborative adaptive behaviors for low-cost robots (mechanical arms) to examine the human response;
  2. using a low-cost Brain-Computer Interface device to gather affective and cognitive data from humans while realizing manufacturing tasks;
  3. building a model that identifies relevant affective and cognitive states and triggers robot behaviors; and
  4. exploring the potential of this approach for skilled and unskilled human users.


Funded by the 2024-2025 Noyce School of Applied Computing Grant and the Summer Undergraduate Research Program (SURP) from the College of Engineering (CENG); and the Believe, Educate & Empower, Advocate, Collaborate, Nurture (BEACoN) program run by the Office of University Diversity and Inclusion.