Robots, often showcased as paragons of precision and seamless collaboration with humans, present an idealized portrayal of human-robot interactions. However, the reality diverges significantly, as robots encounter failures that lead to misunderstandings and socially awkward situations. Conversely, human-induced errors in these interactions often go undetected by robots, amplifying the complexity of the interaction dynamics.
In both research and industry, errors – wrong actions that are made due to the lack of knowledge – and mistakes – actions that turn out to be wrong – in human-robot interactions are commonly viewed as impediments to achieving flawless collaboration. Scholars and practitioners aspire to meticulously control variables, creating environments with predictable storylines and outcomes. Nevertheless, the controlled setting of a laboratory rarely mirrors the unpredictable nature of real-world scenarios, contributing to a notable disparity between expectations and actual experiences.
Recognizing the substantial gap between anticipated perfection and the inherent uncertainties of real-world applications, we contend that the ability of robots to navigate erroneous situations is paramount for the sustained success of human-robot interactions. Whether errors originate from the robot, the human partner, or unforeseen circumstances, a comprehensive understanding and effective handling of these imperfections are critical.
In light of this perspective, we extend an invitation for scholarly contributions on the theme of "Errors and Mistakes in Human-Robot Interactions." Submissions are encouraged to explore various facets, such as the development of robots capable of managing imperfect interactions, the impact of misunderstandings and social norm violations on the perception of robots, and the automation of methods for detecting errors in human-robot interactions.
This Research Topic aims to foster a nuanced discussion within the research community, delving into the complexities of human-robot interactions and embracing the imperfections inherent in these collaborations. We invite researchers and practitioners to contribute their insights, ultimately advancing our understanding and paving the way for more resilient and adaptable human-robot partnerships.
The topics of interest include, but are not limited to:
- Errors in HRI and their impact on user's trust
- User experience with erroneous robots
- Automated detection of errors / unforeseen situations
- Error recovery and explanation in HRI
- Unexpected / flawed robot behaviors
- Socially awkward robots
- Learning from imperfect or incomplete data
- Addressing robot errors through iterative design
- Lessons for error recovery from longitudinal and in-the-wild HRI
- Abandonment or attrition in use of robots caused by errors
- Models for robots to adapt to errors when interacting with humans
Robots, often showcased as paragons of precision and seamless collaboration with humans, present an idealized portrayal of human-robot interactions. However, the reality diverges significantly, as robots encounter failures that lead to misunderstandings and socially awkward situations. Conversely, human-induced errors in these interactions often go undetected by robots, amplifying the complexity of the interaction dynamics.
In both research and industry, errors – wrong actions that are made due to the lack of knowledge – and mistakes – actions that turn out to be wrong – in human-robot interactions are commonly viewed as impediments to achieving flawless collaboration. Scholars and practitioners aspire to meticulously control variables, creating environments with predictable storylines and outcomes. Nevertheless, the controlled setting of a laboratory rarely mirrors the unpredictable nature of real-world scenarios, contributing to a notable disparity between expectations and actual experiences.
Recognizing the substantial gap between anticipated perfection and the inherent uncertainties of real-world applications, we contend that the ability of robots to navigate erroneous situations is paramount for the sustained success of human-robot interactions. Whether errors originate from the robot, the human partner, or unforeseen circumstances, a comprehensive understanding and effective handling of these imperfections are critical.
In light of this perspective, we extend an invitation for scholarly contributions on the theme of "Errors and Mistakes in Human-Robot Interactions." Submissions are encouraged to explore various facets, such as the development of robots capable of managing imperfect interactions, the impact of misunderstandings and social norm violations on the perception of robots, and the automation of methods for detecting errors in human-robot interactions.
This Research Topic aims to foster a nuanced discussion within the research community, delving into the complexities of human-robot interactions and embracing the imperfections inherent in these collaborations. We invite researchers and practitioners to contribute their insights, ultimately advancing our understanding and paving the way for more resilient and adaptable human-robot partnerships.
The topics of interest include, but are not limited to:
- Errors in HRI and their impact on user's trust
- User experience with erroneous robots
- Automated detection of errors / unforeseen situations
- Error recovery and explanation in HRI
- Unexpected / flawed robot behaviors
- Socially awkward robots
- Learning from imperfect or incomplete data
- Addressing robot errors through iterative design
- Lessons for error recovery from longitudinal and in-the-wild HRI
- Abandonment or attrition in use of robots caused by errors
- Models for robots to adapt to errors when interacting with humans