Human-robot cross-training: Computational formulation, modeling and evaluation of a human team training strategy

By Stefanos Nikolaidis, Julie Arnold Shah. 2013

198 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Social Psychology

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Citations in the corpus

Improving Robot Controller Transparency Through Autonomous Policy Explanation (2017, background): “Study results have indicated that achieving comprehension of control logic leads to improved team performance [46, 28, 39] and prevention of automation abuse [30].”
Anticipating Human Activities Using Object Affordances for Reactive Robotic Response (2013, background): “Such scenarios happen in several other settings, for example, manufacturing scenarios in future co-robotic settings (e.g., [8], [9]).”
On the Utility of Learning about Humans for Human-AI Coordination (2019, background): “Much work focuses on achieving collaboration by planning and learning with (non-optimal) models of human behavior [26, 21, 31], as well as on specific properties of robot behavior that aid collaboration [2, 14, 9].”
A survey of robot learning from demonstrations for Human-Robot Collaboration (2017, methodology): “Stefanos Nikolaidis and Julie Shah introduced an interactive training method, which is called Cross-training , for improving human-robot teamwork [34].”
Learning preferences for manipulation tasks from online coactive feedback (2015, background): “Recent works by Nikolaidis et al. [39, 40] in human-robot collaboration learns human preferences over a sequence of sub-tasks in assembly line manufacturing.”
Initiative in robot assistance during collaborative task execution (2016, background): “, circuit building [1], lego model assembly [23], food preparation [5], industrial assembly [4]), including partially ordered action sequencing and shared physical space.”
Learning with Humans in the Loop (2020, methodology): “For robots and interaction, methods from all three paradigms exist: model-free [44, 11, 48], regular model-based [52], and ToM-based [68, 18, 6, 30, 51].”
Evaluating Fluency in Human–Robot Collaboration (2019, methodology): “In [8], authors used individual indicators from the “trust in robot” measure and adapted two indicators from the WAI “goal” subscale.”
Shared autonomy via hindsight optimization for teleoperation and teaming (2017, methodology): “Inspired by training schemes for human-human teams, Nikolaidis and Shah (2013) present a human-robot cross training method, where the user and robot iteratively switch roles to learn a shared plan.”
Challenges in Shared-Environment Human-Robot Collaboration (2013, unknown): “the process, engendering trust between workers [32].”
How Robot Verbal Feedback Can Improve Team Performance in Human-Robot Task Collaborations (2015, methodology): “This formulation has been successfully used previously in human-robot collaboration [15] to coordinate the task-actions of the robot without any communicative feedback.”