Trouble-based group dynamics in real-world HRI &amp;#x2014; Reactions on unexpected next moves of a museum guide robot

Gehle, Raphaela; Pitsch, Karola; Dankert, Timo; Wrede, Sebastian

doi:10.1109/roman.2015.7333574

Cited by 12 publications

(15 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Almost all errors researched in the literature exemplified technical failures (e.g., Gieselmann, 2006 ; Kim and Hinds, 2006 ; Gieselmann and Ostendorf, 2007 ; Spexard et al, 2008 ; Kim et al, 2009 ; Groom et al, 2010 ; Lee et al, 2010 ; Takayama et al, 2011 ; Desai et al, 2012 , 2013 ; Kahn et al, 2012 ; Rosenthal et al, 2012 ; Shiomi et al, 2013 ; Yasuda and Matsumoto, 2013 ; Kaniarasu and Steinfeld, 2014 ; Lohan et al, 2014 ; Cha et al, 2015 ; Gehle et al, 2015 ; Giuliani et al, 2015 ; Gompei and Umemuro, 2015 ; Hamacher, 2015 ; Knepper et al, 2015 ; Mirnig et al, 2015 , 2017 ; Mubin and Bartneck, 2015 ; Salem et al, 2015 ; Bajones et al, 2016 ; Brooks et al, 2016 ; Hamacher et al, 2016 ; Hayes et al, 2016 ; Ragni et al, 2016 ; Robinette et al, 2016 ; Engelhardt and Hansson, 2017 ; Law et al, 2017 ; Sarkar et al, 2017 ; van der Woerdt and Haselager, 2017 ; Kwon et al, 2018 ). Only a few evaluated the impact of social norm violations (e.g., Short et al, 2010 ; Salem et al, 2013 ; Giuliani et al, 2015 ; Mirnig et al, 2015 , 2017 ; van der Woerdt and Haselager, 2017 ), and none focused on human errors.…”

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

“…A robot's failure symptoms in the literature include the robot not completing a given task (e.g., Takayama et al, 2011 ; Rosenthal et al, 2012 ; Brooks et al, 2016 ; Robinette et al, 2016 ; Mirnig et al, 2017 ; Kwon et al, 2018 ), running into obstacles (e.g., Brooks et al, 2016 ), performing the wrong action (e.g., Kim et al, 2009 ; Lee et al, 2010 ; Desai et al, 2012 , 2013 ; Yasuda and Matsumoto, 2013 ; Kaniarasu and Steinfeld, 2014 ; Gehle et al, 2015 ; Mubin and Bartneck, 2015 ; Salem et al, 2015 ; Brooks et al, 2016 ; Hayes et al, 2016 ; Robinette et al, 2016 ; Mirnig et al, 2017 ; Sarkar et al, 2017 ; van der Woerdt and Haselager, 2017 ), performing the right action incorrectly or incompletely (e.g., Takayama et al, 2011 ; Shiomi et al, 2013 ; Cha et al, 2015 ; Hamacher, 2015 ; Brooks et al, 2016 ; Hamacher et al, 2016 ; Adubor et al, 2017 ; Sarkar et al, 2017 ; van der Woerdt and Haselager, 2017 ; Kwon et al, 2018 ), producing no action or speech (irresponsiveness) (e.g., Gieselmann, 2006 ; Lohan et al, 2014 ; Bajones et al, 2016 ; Robinette et al, 2016 ; Lucas et al, 2017 , 2018 ), timing speech improperly (e.g., Mirnig et al, 2017 ), failing to produce speech (e.g., Gieselmann and Ostendorf, 2007 ; Mirnig et al, 2017 ), producing inappropriate speech or erroneous instruction (e.g., Gieselmann, 2006 ; Gieselmann and Ostendorf, 2007 ; Short et al, 2010 ; Gehle et al, 2015 ; Gompei and Umemuro, 2015 ; Lucas et al, 2017 , 2018 ; Mirnig et al, 2017 ; Sarkar et al, 2017 ), repeating s...…”

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

“…Error recovery strategies and reactions to errors have been evaluated using surveys (e.g., Lee et al, 2010 ; Takayama et al, 2011 ; Cha et al, 2015 ; Brooks et al, 2016 ; Adubor et al, 2017 ; Kim et al, 2017 ; Rossi et al, 2017b ; van der Woerdt and Haselager, 2017 ; Kwon et al, 2018 ), video analysis of HRIs (e.g., Giuliani et al, 2015 ; Mirnig et al, 2015 ), and unstructured observational studies (e.g., Gieselmann, 2006 ; Gehle et al, 2015 ), however most studies used controlled user experiments (e.g., Spexard et al, 2008 ; Short et al, 2010 ; Desai et al, 2013 ; Salem et al, 2013 , 2015 ; Gompei and Umemuro, 2015 ; Knepper et al, 2015 ; Hayes et al, 2016 ; Ragni et al, 2016 ; Robinette et al, 2016 ; Mirnig et al, 2017 ; Lucas et al, 2018 ). One study introduced an idea on how to improve situation awareness (SA; see Comprehension and Memory section) in erroneous situations without any formal evaluation (Cassenti, 2007 ).…”

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

See 2 more Smart Citations

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

2018

View full text Add to dashboard Cite

While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI), and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI), human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP), that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1) communicating failures, (2) perception and comprehension of failures, and (3) solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a tool to promote the development of user-centered failure-handling strategies for HRIs.

show abstract

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

See 1 more Smart Citation

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

2018

View full text Add to dashboard Cite

show abstract

“…While in their approach errors are recognized through the robot's internal state and the environment (e.g., the robot is supposed to pick up an object which it can visually detect, but the object is out of its reach), we envision an approach where the robot can additionally detect an error through its human interaction partner's social signals. For example, Gehle et al (2015) explored gaze patterns of human groups upon unexpected robot behavior in a museum guide scenario. They found that groups of visitors responded to unexpected robot behavior with stepwise gaze coordination, applying different modes of gaze constellation.…”

Section: Introductionmentioning

confidence: 99%

To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot

et al. 2017

View full text Add to dashboard Cite

We conducted a user study for which we purposefully programmed faulty behavior into a robot's routine. It was our aim to explore if participants rate the faulty robot different from an error-free robot and which reactions people show in interaction with a faulty robot. The study was based on our previous research on robot errors where we detected typical error situations and the resulting social signals of our participants during social human-robot interaction. In contrast to our previous work, where we studied video material in which robot errors occurred unintentionally, in the herein reported user study, we purposefully elicited robot errors to further explore the human interaction partners' social signals following a robot error. Our participants interacted with a human-like NAO, and the robot either performed faulty or free from error. First, the robot asked the participants a set of predefined questions and then it asked them to complete a couple of LEGO building tasks. After the interaction, we asked the participants to rate the robot's anthropomorphism, likability, and perceived intelligence. We also interviewed the participants on their opinion about the interaction. Additionally, we video-coded the social signals the participants showed during their interaction with the robot as well as the answers they provided the robot with. Our results show that participants liked the faulty robot significantly better than the robot that interacted flawlessly. We did not find significant differences in people's ratings of the robot's anthropomorphism and perceived intelligence. The qualitative data confirmed the questionnaire results in showing that although the participants recognized the robot's mistakes, they did not necessarily reject the erroneous robot. The annotations of the video data further showed that gaze shifts (e.g., from an object to the robot or vice versa) and laughter are typical reactions to unexpected robot behavior. In contrast to existing research, we assess dimensions of user experience that have not been considered so far and we analyze the reactions users express when a robot makes a mistake. Our results show that decoding a human's social signals can help the robot understand that there is an error and subsequently react accordingly.

show abstract

“…We will explore the question of limits and opportunities in mathematizing communicational conduct using the example of a robotic museum guide deployed at the Bielefeld Historical Museum in September 2014 (see also Gehle et al 2015). A humanoid NAO robot was positioned on a table (1.20 9 2 m, 0.7 m high) and set up to autonomously engage in a focused encounter with visitors and to give explanations about several exhibits by using talk, head and arm gestures and walking across the table (see images of the setting below).…”

Section: Introductionmentioning

confidence: 99%

Limits and opportunities for mathematizing communicational conduct for social robotics in the real world? Toward enabling a robot to make use of the human’s competences

Trouble-based group dynamics in real-world HRI — Reactions on unexpected next moves of a museum guide robot

Cited by 12 publications

References 10 publications

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot

Limits and opportunities for mathematizing communicational conduct for social robotics in the real world? Toward enabling a robot to make use of the human’s competences

Contact Info

Product

Resources

About