Learning the communication of intent prior to physical collaboration

Strabala, Kyle; Lee, Min Kyung; Dragan, Anca D.; Forlizzi, Jodi; Srinivasa, Siddhartha S.

doi:10.1109/roman.2012.6343875

Cited by 46 publications

(40 citation statements)

References 17 publications

(16 reference statements)

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“…In our second study (Strabala, Lee, Dragan, Forlizzi, & Srinivasa, 2012), we observed 27 human pairs performing a task that required handovers. The participants were placed in a kitchen environment and tasked with putting away a bag of groceries and packing a picnic basket.…”

Section: Learning the Communication Of Intentmentioning

confidence: 99%

“…in Fig.2, first split is on > 0.25 vs. ≤ 0.25). A high value (closer to 1.0) indicates a higher match between the interaction and the feature (details in (Strabala et al, 2012)). The figure also shows, for each brach, the percentage of the total data for signals (green) and non-signals (red).…”

Section: Learning the Communication Of Intentmentioning

confidence: 99%

“…For the experiments presented in this section, we implemented and evaluated several versions of handover behaviors on our robot HERB (Home Exploring Robot Butler) (Srinivasa et al, 2012). HERB was specifically developed for personal assistance in domestic tasks.…”

Section: Human-robot Handoversmentioning

confidence: 99%

“…However, tuning the gains of the controller without making the robot too aggressive is challenging, and a complete redesign of the controller behavior could be necessary to obtain more effective human robot handovers. Another way to make the handover faster could be detecting the intent to handover an object before the human arm motion begins as shown in (Strabala et al, 2012).…”

Section: Taking Objects Handed By Humansmentioning

confidence: 99%

See 3 more Smart Citations

Towards Seamless Human-Robot Handovers

Strabala

Lee

Dragan

et al. 2013

JHRI

Self Cite

219

147

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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 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.

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Section: Learning the Communication Of Intentmentioning

confidence: 99%

Section: Learning the Communication Of Intentmentioning

confidence: 99%

Section: Human-robot Handoversmentioning

confidence: 99%

Section: Taking Objects Handed By Humansmentioning

confidence: 99%

See 2 more Smart Citations

Towards Seamless Human-Robot Handovers

Strabala

Lee

Dragan

et al. 2013

JHRI

Self Cite

219

147

View full text Add to dashboard Cite

show abstract

“…Their later work [41] used various pre-handover cues-such as proxemics, pose and gaze-to predict handover intent. In our work, we focused on the impact of robot gaze behaviors during the handover, after the handover intent has been clearly understood by both the giver and the receiver.…”

Section: Robot Gaze and Handover In Hrimentioning

confidence: 99%

Impacts of Robot Head Gaze on Robot-to-Human Handovers

Zheng

Moon

Croft

et al. 2015

Int J of Soc Robotics

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In this paper, we investigate the use of a robot's gaze to improve the timing and subjective experience of faceto-face robot-to-human handovers. Based on observations of human gaze behaviors during face-to-face human-human handovers, we implement various gaze behaviors on a PR2 humanoid robot. We conducted two consecutive robot-tohuman handover studies. Results show that when the robot continually gazes at a projected handover position while handing over an object, the human receivers reach for the object significantly earlier than when the robot looks down, away from the handover location; further, when the robot continually gazes at the receiver's face instead of the handover position, the receivers reach for the object even earlier. When the robot-instead of continually gazing at a location-transitions its gaze from the handover position to the receivers' face, or vice versa, the receivers' reach time did not improve; however, the receivers perceive these gaze transitions to better communicate handover timing than continual gazes. Finally, the receivers perceive the robot to be more likeable and anthropomorphic when it looks at their B Minhua Zheng face than when it does not. Findings from our studies indicate that robot's use of gaze can help improve both fluency and subjective experience of the robot-to-human handover interactions.

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