Toward seamless human-robot handovers

By Kyle Strabala, Min Kyung Lee, Anca Dragan, Jodi L. Forlizzi, Siddhartha S. Srinivasa, Maya Cakmak, Vincenzo Micelli. 2013

303 citations recorded by the source corpus.

A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of performing handovers seamlessly in a wide variety of situations, even when unexpected. This suggests a common procedure that guides all handover interactions. Our goal is to codify that procedure. To that end, we first study how people hand over objects to each other in order to understand their coordination process and the signals and cues that they use and observe with their partners. Based on these studies, we propose a coordination structure for human-robot handovers that considers the physical and social-cognitive aspects of the interaction separately. This handover structure describes how people approach, reach out their hands, and transfer objects while simultaneously coordinating the what, when, and where of handovers: to agree that the handover will happen (and with what object), to establish the timing of the handover, and to decide the configuration at which the handover will occur. We experimentally evaluate human-robot handover behaviors that exploit this structure and offer design implications for seamless human-robot handover interactions.

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

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Citations in the corpus

Social eye gaze in human-robot interaction (2017, background): “When they must pass objects back and forth, object handovers between people rely on a receiver signaling readiness to receive an object by gazing at their partner (Strabala, Lee, Dragan, Forlizzi, & Srinivasa, 2012; Strabala et al., 2013).”
Coordination in human-robot teams using mental modeling and plan recognition (2014, background): “There has been a variety of prior work in developing coordination and prediction capabilities for human-robot interaction in joint tasks involving physical interaction, such as assembly scenarios [5] and object handovers [6].”
Recent Advances in Robot Learning from Demonstration (2020, background): “Specifically, LfDmethods have helped teach manipulators a variety of skills, such as feeding (160), physical rehabilitation (161), robotic surgery (85, 162), assisting children with cerebral palsy (163), supporting daily activities (164), hand rehabilitation (165), handing over objects (166), and mo”
Challenges in Shared-Environment Human-Robot Collaboration (2013, background): “Existing approaches rely upon attempting to characterize significant features used in human-to-human collaborative activities, such as handover tasks [25], [26].”