Design and Impact of Hesitation Gestures during Human-Robot Resource Conflicts

Moon, AJung; Parker, Chris A. C.; Croft, Elizabeth A.

doi:10.5898/jhri.2.3.moon

Cited by 31 publications

(22 citation statements)

References 37 publications

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“…Similar to the presented study, Moon et al [36] found less evidence in objective measures like human performance than in subjective measures, where participants regarded the movements as hesitations. The authors did not find sufficient evidence that the hesitation motion profile improved human-robot task completion time, while results suggested that participants can recognize such robot responses as hesitations and distinguished them from abrupt stopping behaviours.…”

Section: Implications Of the Video Studysupporting

confidence: 84%

Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction

Reinhardt¹,

Prasch²,

Bengler³

2020

Preprint

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Standstill behavior by a robot is deemed to be ineffective and inefficient to convey a robot’s intention to yield priority to another party in spatial interaction. Instead, robots could convey their intention and, thus, their next action via motion. We developed a back-off movement to communicate the intention of yielding priority to pedestrians at bottlenecks. To evaluate human sensory perception and subjective legibility, the back-off is compared to three other motion strategies in a video study with N = 167 interviewees at the university and public spaces, where it excels regarding legibility. Implemented in a real encounter, objective motion behavior of N = 78 participants as a reaction to a stop & wait strategy, and two versions of back-off (short and long) shows an improvement of the pedestrians’ efficiency in the second encounter with the robot’s short back-off version compared to the stop strategy. Eventually, in the third encounter with all motion strategies, interaction causes only a small time consumption still required by the cognitive process of perceiving an object in the visual field. Hence, the design of kinematic parameters, back-off path and time, exhibits the potential to increase the fluency of an interaction with robots at bottlenecks.

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Section: Implications Of the Video Studysupporting

confidence: 84%

Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction

Reinhardt¹,

Prasch²,

Bengler³

2020

Preprint

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show abstract

“…Studies have shown clear correlations between musical features and movement features, suggesting that a single model can be used to express emotion through both music and movement [31], [32], [33]. Certain characteristics of robotic motion have been shown to influence human emotional response [34], [35]. Additionally, emotional intelligence in robots leads to facilitated human-robot interactions [36], [25], [37].…”

Section: Emotion Music and Gesturementioning

confidence: 99%

Establishing Human-Robot Trust through Music-Driven Robotic Emotion Prosody and Gesture

Savery

Rose

Weinberg

2019

2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

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As human-robot collaboration opportunities continue to expand, trust becomes ever more important for full engagement and utilization of robots. Affective trust, built on emotional relationship and interpersonal bonds is particularly critical as it is more resilient to mistakes and increases the willingness to collaborate. In this paper we present a novel model built on music-driven emotional prosody and gestures that encourages the perception of a robotic identity, designed to avoid uncanny valley. Symbolic musical phrases were generated and tagged with emotional information by human musicians. These phrases controlled a synthesis engine playing back prerendered audio samples generated through interpolation of phonemes and electronic instruments. Gestures were also driven by the symbolic phrases, encoding the emotion from the musical phrase to low degree-of-freedom movements. Through a user study we showed that our system was able to accurately portray a range of emotions to the user. We also showed with a significant result that our non-linguistic audio generation achieved an 8% higher mean of average trust than using a state-of-the-art text-to-speech system.

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“…After each block and at the experiments' end, participants answered questions about their impressions of the robot, collaborative quality, and method comparisons ( Table 2). Parts of the questionnaire were adapted from Bartneck, Kulić, Croft, & Zoghbi (2008) and Moon, Parker, Croft, & Van der Loos (2013).…”

Section: Metricsmentioning

confidence: 99%

Tap and Push: Assessing the Value of Direct Physical Control in Human-Robot Collaborative Tasks

Gleeson¹,

Currie²,

MacLean³

et al. 2015

Journal of Human-Robot Interaction

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In this paper, we compare a touch-based human-to-robot command scheme with traditional button commands in a series of human-robot collaborative assembly tasks. We find a mapping between command style and task outcome that depends on task complexity and is influenced by robot "feel." In our direct touch-based scheme, the user commands the robot through direct physical contact by tapping and pushing the robot. With a small, compliant desktop robot and a simple, scripted, bolt insertion task, button commands performed slightly better than direct physical commands in quantitative task performance metrics and qualitative user preference. In a second study with a human-scale, stiffer robot arm, physical commands performed better than button commands in a more complex and less scripted bolt insertion task, which greatly outperformed using buttons in a cooperative positioning task. We conclude that commanding a robot through direct force-transmitting contact can decrease task completion time, aid in teamwork, and improve user experience in appropriately chosen tasks. We achieve our haptic commands using only robot position sensors, demonstrating that direct, intuitive physical command is an option for existing position-controlled industrial robots.

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Design and Impact of Hesitation Gestures during Human-Robot Resource Conflicts

Cited by 31 publications

References 37 publications

Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction

Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction

Establishing Human-Robot Trust through Music-Driven Robotic Emotion Prosody and Gesture

Tap and Push: Assessing the Value of Direct Physical Control in Human-Robot Collaborative Tasks

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