Expressing Robot Incapability

Kwon, Minae; Huang, Sandy H.; Dragan, Anca D.

doi:10.1145/3171221.3171276

Cited by 86 publications

(61 citation statements)

References 30 publications

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“…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%

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

2018

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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.

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Section: Literature Review On User-centered Failure Handlingmentioning

confidence: 99%

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

2018

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“…Legible motion is used by humans working in close proximity, and so can also be useful and important for situations in which a physically embodied AIA and person are collaboratively working in close proximity to each other. Similarly, in more recent work Kwon et al [76] investigates calculating trajectories that convey 'incapability', which is what the AIA is trying to do, and why it is unable to do so. See also [3] for related work.…”

Section: Commonmentioning

confidence: 99%

“…• e UGV has been designed with the ability to use gestures in order to indicate its 'incapability' as in [76] As the UGV begins the escort problem, the human supervisor is monitoring progress. When the UGV reaches a certain intersection of the road network the supervisor expects the UGV to take a path A, but it does not.…”

Section: • E Operator Can Observe All the Actions Of The Ugv Via Vidementioning

confidence: 99%

“Dave...I can assure you ...that it’s going to be all right ...” A Definition, Case for, and Survey of Algorithmic Assurances in Human-Autonomy Trust Relationships

Israelsen

Ahmed

2019

ACM Comput. Surv.

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People who design, use, and are a ected by autonomous arti cially intelligent agents want to be able to trust such agents -that is, to know that these agents will perform correctly, to understand the reasoning behind their actions, and to know how to use them appropriately. Many techniques have been devised to assess and in uence human trust in arti cially intelligent agents. However, these approaches are typically ad hoc, and have not been formally related to each other or to formal trust models. is paper presents a survey of algorithmic assurances, i.e. programmed components of agent operation that are expressly designed to calibrate user trust in arti cially intelligent agents. Algorithmic assurances are rst formally de ned and classi ed from the perspective of formally modeled human-arti cially intelligent agent trust relationships. Building on these de nitions, a synthesis of research across communities such as machine learning, human-computer interaction, robotics, e-commerce, and others reveals that assurance algorithms naturally fall along a spectrum in terms of their impact on an agent's core functionality, with seven notable classes ranging from integral assurances (which impact an agent's core functionality) to supplemental assurances (which have no direct e ect on agent performance).Common approaches within each of these classes are identi ed and discussed; bene ts and drawbacks of di erent approaches are also investigated.

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“…In the optimization-based approach, the expressive objective is explicitly formulated as a cost function, which is then optimized to generate the most expressive trajectory. This approach has been applied to a variety of expressive styles, including legibility [20,86], deception [19], emotion [23], style [58], and robot incapability [50].…”

Section: Formulatedmentioning

confidence: 99%

Robot Expressive Motions

Venture

Kulić

2019

J. Hum.-Robot Interact.

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Robots that have different forms and capabilities are used in a wide variety of situations; however, one common point to all robots interacting with humans is their ability to communicate with them. In addition to verbal communication or purely communicative movements, robots can also use their embodiment to generate expressive movements while achieving a task, to convey additional information to its human partner. This article surveys state-of-the-art techniques that generate whole-body expressive movements in robots and robot avatars. We consider different embodiments such as wheeled, legged, or flying systems and the different metrics used to evaluate the generated movements. Finally, we discuss future areas of improvement and the difficulties to overcome to develop truly expressive motions in artificial agents.

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Expressing Robot Incapability

Cited by 86 publications

References 30 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

“Dave...I can assure you ...that it’s going to be all right ...” A Definition, Case for, and Survey of Algorithmic Assurances in Human-Autonomy Trust Relationships

Robot Expressive Motions

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