Hand in Hand with Robots: Differences Between Experienced and Naive Users in Human-Robot Handover Scenarios

Borgsen, Sebastian Meyer zu; Bernotat, Jasmin; Wachsmuth, Sven

doi:10.1007/978-3-319-70022-9_58

Cited by 13 publications

(7 citation statements)

References 25 publications

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“…Meka is a humanoid system with two dexterous arms and hands, an omnidirectional wheelbase, and an exchangeable rectangleshaped sensor head. Meka can navigate through the environment, detect and grasp objects (see [21], [22]). Quite contrary to Flobi, Meka's sensor head is wider relative to its height and does not provide any social cues to display emotions or to facilitate social communication.…”

Section: Introductionmentioning

confidence: 99%

Can(‘t) Wait to Have a Robot at Home? - Japanese and German Users' Attitudes Toward Service Robots in Smart Homes

Bernotat

Eyssel

2018

2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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In the present study, we compared Japanese and German participants' perceptions of social robots. To do so, participants from both cultural backgrounds evaluated two types of service robots designed for use in the smart home context. One of the prototypes featured a rather technical appearance, whereas the other prototype featured a newly designed social robot head. Against our predictions, Japanese and German participants evaluated both robot types similarly. Japanese participants generally showed a stronger tendency to anthropomorphize nonhuman agents and attributed more mind, particularly on the experience dimension, to both robot types than German participants. Nonetheless, Japanese and German participants attributed similar levels of agency to both robot types. Unexpectedly, Japanese participants perceived the robots even as less humanlike than German participants. As predicted, Japanese participants reported less attitudinal robot acceptance and tended to show less trust toward both robot types than Germans. Japanese and Germans indicated similar levels of robot anxiety, perceived uncanniness, and robot likeability. Japanese and German participants generally perceived the robots rather as machines and tools than as human companions. Especially German participants wanted to use the robots for rather safe, boring, and simple tasks that do not require any direct interaction with them. Japanese and German participants were not yet familiar with robots and showed less positive attitudes toward them than widely believed (e.g., [1]). Implications how to gain a more realistic view on users' perceptions of robots to enable a fruitful and comfortable HRI are discussed. *This research was supported by the Cluster of Excellence Cognitive Interaction Technology 'CITEC' (EXC 277) at Bielefeld University, which is funded by the German Research Foundation (DFG). It is further related to the European Project CODEFROR (FP7-PIRSES-2013-612555). might perceive robots differently: Shinto and Buddhism are prevalent religions in Japan, while German culture is influenced by Christianity. A Shinto legend holds that Japanese islands were formed by two gods who became progenitors of the gods of Shinto religion and of the first Emperor of Japan [3]. This belief resulted in a deep respect for nature, animals, gods, and heroes. Further, Japanese people believe that a soul, humanlike traits, and intentions are inherent in any entity, such as in gods, heroes, animals, and nature. This is also reflected in Japanese popular culture in which various kinds of nonhuman agents, including robots, are presented as having humanlike traits [4]. According to [5], anthropomorphism, the tendency to ascribe human traits to nonhuman agents, helps to understand others' behavior and thus might reduce uncertainty. Accordingly, one might assume that the tendency to anthropomorphize nonhuman agents and the prevalence of robots in Japanese popular culture is linked to more positive evaluations of HRI and less anxiety toward robots than in Western countries. H...

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Section: Introductionmentioning

confidence: 99%

Can(‘t) Wait to Have a Robot at Home? - Japanese and German Users' Attitudes Toward Service Robots in Smart Homes

Bernotat

Eyssel

2018

2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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“…They also suggested that the best handover intent is conveyed by an almost extended arm [10]. A study of effect of participant's previous encounters with robots on human-robot handovers showed that naive users, as opposed to experienced ones, expect the robot to monitor the handover visually, rather than merely use the force sensor [11]. A study of the impact of repeated handover experiments on the robot's social perception [12] showed that participants' emotional warmth towards the robot and comfort were improved by repeated experiments.…”

Section: Human-to-robot Handoversmentioning

confidence: 99%

Human Preferences for Robot Eye Gaze in Human-to-Robot Handovers

Faibish

Kshirsagar

Hoffman

et al. 2022

Int J of Soc Robotics

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This paper investigates human's preferences for a robot's eye gaze behavior during human-to-robot handovers. We studied gaze patterns for all three phases of the handover process: reach, transfer, and retreat, as opposed to previous work which only focused on the reaching phase. Additionally, we investigated whether the object's size or fragility or the human's posture affect the human's preferences for the robot gaze. A public data-set of human-human handovers was analyzed to obtain the most frequent gaze behaviors that human receivers perform. These were then used to program the robot's receiver gaze behaviors. In two sets of user studies (video and in-person), a collaborative robot exhibited these gaze behaviors while receiving an object from a human. In the video studies, 72 participants watched and compared videos of handovers between a human actor and a robot demonstrating each of the three gaze behaviors. In the in-person studies, a different set of 72 participants physically performed object handovers with the robot and evaluated their perception of the handovers for the robot's different gaze behaviors. Results showed that, for both observers and participants in a handover, when the robot exhibited Face-Hand-Face gaze (gazing at the giver's face and then at the giver's hand during the reach phase and back at the giver's face during the retreat phase), participants considered the handover to be more likable, anthropomorphic, and communicative of timing ( p < 0.0001). However, we did not find evidence of any effect of the object's size or fragility or the giver's posture on the gaze preference. KeywordsHuman-robot handovers • Human-robot interaction • Robot eye gaze • Human-human-handovers • Non-verbal communication Tair Faibish and Alap Kshirsagar contributed equally to this work.

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“…A number of user studies have been conducted to validate different handover approaches and provide empirical evidence, such as people's preference among alternative ways of handing objects [15], [18], impact of robot behaviors such as gaze [35], [36], or difference between novice and experienced users [37]. Some work has explored humanhuman handovers to characterize movement properties [38], [39], [40], grip force patterns [41], use of social cues [42], or failure recovery strategies [43].…”

Section: Related Workmentioning

confidence: 99%

Human Grasp Classification for Reactive Human-to-Robot Handovers

Yang

Paxton

Çakmak

et al. 2020

Preprint

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Transfer of objects between humans and robots is a critical capability for collaborative robots. Although there has been a recent surge of interest in human-robot handovers, most prior research focus on robot-to-human handovers. Further, work on the equally critical human-to-robot handovers often assumes humans can place the object in the robot's gripper. In this paper, we propose an approach for human-to-robot handovers in which the robot meets the human halfway, by classifying the human's grasp of the object and quickly planning a trajectory accordingly to take the object from the human's hand according to their intent. To do this, we collect a human grasp dataset which covers typical ways of holding objects with various hand shapes and poses, and learn a deep model on this dataset to classify the hand grasps into one of these categories. We present a planning and execution approach that takes the object from the human hand according to the detected grasp and hand position, and replans as necessary when the handover is interrupted. Through a systematic evaluation, we demonstrate that our system results in more fluent handovers versus two baselines. We also present findings from a user study (N = 9) demonstrating the effectiveness and usability of our approach with naive users in different scenarios. More results and videos can be found at http://wyang.me/handovers.

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Hand in Hand with Robots: Differences Between Experienced and Naive Users in Human-Robot Handover Scenarios

Cited by 13 publications

References 25 publications

Can(‘t) Wait to Have a Robot at Home? - Japanese and German Users' Attitudes Toward Service Robots in Smart Homes

Can(‘t) Wait to Have a Robot at Home? - Japanese and German Users' Attitudes Toward Service Robots in Smart Homes

Human Preferences for Robot Eye Gaze in Human-to-Robot Handovers

Human Grasp Classification for Reactive Human-to-Robot Handovers

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