Common metrics for human-robot interaction

By Aaron Steinfeld, T. Fong, David B. Kaber, Michael Lewis, Jean C. Scholtz, Alan C. Schultz, Michael A. Goodrich. IEEE/ACM International Conference on Human-Robot Interaction, 2006

879 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Social Psychology, Surgery

View Paper: https://www.semanticscholar.org/paper/9fa8ec3c4d9089ee70e1add57297e5bf14a03d24

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Citations in the corpus

Human Interaction With Robot Swarms: A Survey (2016, background): “This concept is in some sense the converse to neglect tolerance [137], [138] in human-robot interaction (HRI) of independent and non-coordinating robots, where it is assumed that the performance of an individual robot degrades with time, and”
A survey of robot learning from demonstration (2009, neutral): “Several metrics from the Human-Robot Interaction (HRI) community could also be adopted [Steinfeld et al., 2006].”
Human Performance Issues and User Interface Design for Teleoperated Robots (2007, background): “Human performance issues involved in teleoperating unmanned systems generally fall in two categories, i.e., remote perception and remote manipulation, which includes both navigation and manipulation tasks (e.g., grasping, pushing , and payload management) [14].”
Toward a framework for levels of robot autonomy in human-robot interaction (2014, background): “Social interaction with intermediate or fully autonomous robots may be more appropriately assessed by the social characteristics of the robot itself (e.g., appearance, emotion, personality; Breazeal, 2003; Steinfeld et al., 2006).”
Socially intelligent robots: dimensions of human–robot interaction (2007, neutral): “The classification and evaluation of HRIs with respect to the application area is an active area of research (e.g. Yanco & Drury 2002, 2004; Scholtz 2003; Steinfeld et al. 2006).”
Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study (2014, background): “Human-robot interaction (HRI) has also been a popular area of research, but HRI’s focus has been on the runtime behavior of robots and not on the difﬁculties of human users applying software frameworks to robot hardware [19], [12], [20].”
Human–robot interaction review and challenges on task planning and programming (2016, background): “Steinfeld, Fong, and Kaber (2006) classi ﬁ ed the common HRI metrics into those related to (a) the system, (b) the human operator and (c) the robot performance.”
The Perception And Measurement Of Human-robot Trust (2013, background): “Research has continued to address the creation and validation of successful evaluation methods for wide spectrum of HRI issues, including human-robot trust (Steinfeld et al., 2006).”
A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction (2011, background): “For example, the less an individual trusts a robot, the sooner he or she will intervene as it progresses toward task completion (de Visser, Parasuraman, Freedy, Freedy, & Weltman, 2006; Steinfeld et al., 2006).”
Learning Interactively to Resolve Ambiguity in Reference Frame Selection (2020, background): “This makes the robot to behave in an unexpected way, having a negative impact in the user experience, and consequently in the human robot interaction, speciﬁcally in factors like engagement, trust or compliance [19, 20].”