The Benefits of Immersive Demonstrations for Teaching Robots

Jackson, Astrid; Northcutt, Brandon D.; Sukthankar, Gita

doi:10.1109/hri.2019.8673270

Cited by 6 publications

(2 citation statements)

References 20 publications

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“…For example, two papers [172,173] indicated recruitment of participants with "high technology acceptance" but without details on the type of technology. Other studies focused on participants' familiarity with broad subsets of technological products, such as video games [171,174], VR systems [105,175], smartphones [176,177], and social media [178,179]. Some studies covered details about familiarity with specific types of technology, such as the Rviz visualization widget [180], maps in the game Unreal Tournament 2004 [181], and Alternative Augmented Communication (AAC) products [128].…”

Section: Domain Expertisementioning

confidence: 99%

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Seaborn

Barbareschi

Chandra

2023

Int J of Soc Robotics

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Critical voices within and beyond the scientific community have pointed to a grave matter of concern regarding who is included in research and who is not. Subsequent investigations have revealed an extensive form of sampling bias across a broad range of disciplines that conduct human subjects research called “WEIRD”: Western, Educated, Industrial, Rich, and Democratic. Recent work has indicated that this pattern exists within human–computer interaction (HCI) research, as well. How then does human–robot interaction (HRI) fare? And could there be other patterns of sampling bias at play, perhaps those especially relevant to this field of study? We conducted a systematic review of the premier ACM/IEEE International Conference on Human-Robot Interaction (2006–2022) to discover whether and how WEIRD HRI research is. Importantly, we expanded our purview to other factors of representation highlighted by critical work on inclusion and intersectionality as potentially underreported, overlooked, and even marginalized factors of human diversity. Findings from 827 studies across 749 papers confirm that participants in HRI research also tend to be drawn from WEIRD populations. Moreover, we find evidence of limited, obscured, and possible misrepresentation in participant sampling and reporting along key axes of diversity: sex and gender, race and ethnicity, age, sexuality and family configuration, disability, body type, ideology, and domain expertise. We discuss methodological and ethical implications for recruitment, analysis, and reporting, as well as the significance for HRI as a base of knowledge.

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Section: Domain Expertisementioning

confidence: 99%

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Seaborn

Barbareschi

Chandra

2023

Int J of Soc Robotics

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“…Three successively harder tasks, e.g. the cleanup task, the handover task, and the block-stacking, were investigated in Jackson et al [34] to validate a system which uses a virtual reality system display and a Sony PlayStation DualShock 3 wireless controller. It was suggested that the use of such system generated superior demonstrations for a deep neural network without introducing a correspondence problem.…”

Section: Machine Learning In Hrimentioning

confidence: 99%

From Humans and Back: a Survey on Using Machine Learning to both Socially Perceive Humans and Explain to Them Robot Behaviours

Panchea

Ferland

2020

Curr Robot Rep

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Purpose of Review As intelligent robots enter our daily routine, it is important to be equipped with proper adaptable social perception and explainable behaviours. To do so, machine learning (ML) is often employed. This paper intends to find a trend in the way ML methods are used and applied to model human social perception and produce explainable robot behaviours. Recent Findings The literature has shown a substantial advancement in ML methods with application to social perception and explainable behaviours. There are papers which report models for robots to imitate humans and also for humans to imitate robots. Others use classical methods and propose new and/or improved ones which led to better human-robot interaction performances. Summary This paper reports a review on social perception and explainable behaviours based on ML methods. First, we present literature background on these three research areas and finish with a discussion on limitations and future research venues.

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TWOPD: A Novel Approach to Teaching an Introductory Cybersecurity Course

Chhetri

2020

Advances in Intelligent Systems and Computing

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The Benefits of Immersive Demonstrations for Teaching Robots

Cited by 6 publications

References 20 publications

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

From Humans and Back: a Survey on Using Machine Learning to both Socially Perceive Humans and Explain to Them Robot Behaviours

TWOPD: A Novel Approach to Teaching an Introductory Cybersecurity Course

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