Editorial: Errors and mistakes in human-robot interactions

by robots, amplifying the complexity of the interaction dynamics on top of the uncertainties in the 5 environment and interaction contexts.In human-robot interaction (HRI) research, errors -wrong actions that are made due to the lack of 7 knowledge -and mistakes -actions that turn out to be wrong -are commonly viewed as impediments 8 to achieving flawless collaboration. Scholars and practitioners aspire to meticulously control variables, 9 creating environments with predictable storylines and outcomes. Nevertheless, the controlled setting of a 10 laboratory rarely mirrors the unpredictable nature of real-world scenarios, contributing to a notable disparity 11 between expectations and actual experiences. The ability of robots to navigate erroneous situations is 12 paramount to the sustained success of HRI. These imperfections are also perfect learning opportunities for 13 robots to continuously adapt to the ever-shifting complexity and dynamics in real-world HRI.This special topic contains research that addresses the gap between anticipated perfection and the inherent 15 uncertainties in a diverse range of real-world applications. The papers presented here shine light on a 16 variety of aspects ranging from novel technical approaches to repair failures in HRI, to user studies that 17 aim to understand social dimensions of errors in HRI. reveal that humans actively support robots through physical repairs, emotional care, and interpretive help, 32 often shouldering the burden of maintaining interactional continuity and redefining agency in the process.The study "Should Robots Display What They Hear? Mishearing as a Practical Accomplishment" by 34 Rudaz and Licoppe explores how publicly displaying a robot's automatic speech recognition (ASR) resultsinfluences the emergence and resolution of miscommunications in human-robot interaction. Through 36 micro-analytic examination, the research reveals that participants often reinterpreted a robot's action as 37 problematic only after reading the ASR transcript, highlighting how this informational ecology shapes 38 perceptions of interactional failures. The findings suggest that "errors" and "mistakes" are not pre-defined 39 technical or social categories but emerge dynamically through interaction, fundamentally altering how 40 mutual understanding is achieved between humans and robots.