6 citations · 14 across the 17 of their papers we have counts for
12 papers · 1 filter
ERR@HRI 3.0 Challenge: Multimodal Detection of Errors and Anticipation in Human-Robot Interactions
Maria Teresa Parreira, Micol Spitale, Maia Stiber +5
As robots become increasingly integrated into human environments, their ability to detect and respond to errors remains critical for maintaining user trust and interaction quality.…
Calling for Backup: How Children Navigate Successive Robot Communication Failures
Maria Teresa Parreira, Isabel Neto, Filipa Rocha +1
How do children respond to repeated robot errors? While prior research has examined adult reactions to successive robot errors, children's responses remain largely unexplored. In t…
"Why the face?": Exploring Robot Error Detection Using Instrumented Bystander Reactions
Maria Teresa Parreira, Ruidong Zhang, Sukruth Gowdru Lingaraju +7
How do humans recognize and rectify social missteps? We achieve social competence by looking around at our peers, decoding subtle cues from bystanders - a raised eyebrow, a laugh -…
Training Models to Detect Successive Robot Errors from Human Reactions
Shannon Liu, Maria Teresa Parreira, Wendy Ju
As robots become more integrated into society, detecting robot errors is essential for effective human-robot interaction (HRI). When a robot fails repeatedly, how can it know when…
ERR@HRI 2.0 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Conversations
Shiye Cao, Maia Stiber, Amama Mahmood +5
The integration of large language models (LLMs) into conversational robots has made human-robot conversations more dynamic. Yet, LLM-powered conversational robots remain prone to e…
The Robotability Score: Enabling Harmonious Robot Navigation on Urban Streets
Matt Franchi, Maria Teresa Parreira, Fanjun Bu +1
This paper introduces the Robotability Score (), a novel metric that quantifies the suitability of urban environments for autonomous robot navigation. Through expert interviews…
ERR@HRI 2024 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Interactions
Micol Spitale, Maria Teresa Parreira, Maia Stiber +7
Despite the recent advancements in robotics and machine learning (ML), the deployment of autonomous robots in our everyday lives is still an open challenge. This is due to multiple…
A Study on Domain Generalization for Failure Detection through Human Reactions in HRI
Maria Teresa Parreira, Sukruth Gowdru Lingaraju, Adolfo Ramirez-Aristizabal +3
Machine learning models are commonly tested in-distribution (same dataset); performance almost always drops in out-of-distribution settings. For HRI research, the goal is often to…
"How Did They Come Across?" Lessons Learned from Continuous Affective Ratings
Maria Teresa Parreira, Michael J. Sack, Hifza Javed +2
Social distance, or perception of the other, is recognized as a dynamic dimension of an interaction, but yet to be widely explored or understood. Through CORAE, a novel web-based o…
The Bystander Affect Detection (BAD) Dataset for Failure Detection in HRI
Alexandra Bremers, Maria Teresa Parreira, Xuanyu Fang +6
For a robot to repair its own error, it must first know it has made a mistake. One way that people detect errors is from the implicit reactions from bystanders -- their confusion,…
Robot Duck Debugging: Can Attentive Listening Improve Problem Solving?
Maria Teresa Parreira, Sarah Gillet, Iolanda Leite
While thinking aloud has been reported to positively affect problem-solving, the effects of the presence of an embodied entity (e.g., a social robot) to whom words can be directed…
Using Social Cues to Recognize Task Failures for HRI: Overview, State-of-the-Art, and Future Directions
Alexandra Bremers, Alexandria Pabst, Maria Teresa Parreira +1
Robots that carry out tasks and interact in complex environments will inevitably commit errors. Error detection is thus an essential ability for robots to master to work efficientl…