Explainability Needs in Human-Robot Collaboration: A Qualitative Interaction Study on the When, What, and How of Cobot Explanations

Collaborative robots (cobots) are increasingly used in manufacturing, yet their behavior can appear unpredictable to human coworkers, making teamwork less smooth. Explainability has been proposed as a key requirement for fluent human-robot collaboration. However, we still lack a clarity of (i) when cobots should provide explanations, (ii) what information human coworkers seek, and (iii) how explanations should be delivered by cobots during real physical collaboration. This paper reports an exploratory qualitative study of human explanation needs in a real-life bicycle assembly task with a 6-axis cobot arm. Fourteen participants interacted with the cobot that occasionally behaved unexpectedly. Think-aloud protocols and semi-structured interviews, show that users seek continuous information primarily about the cobot's current status and situation-dependent guidance for interaction. Participants favored simple presentations such as easy-to-read text explanations and light signals. We discuss implications for designing explainable cobots that provide lightweight, context-sensitive information and outline directions for future quantitative evaluations.