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This work aims to interpret human behavior to anticipate potential user confusion when a robot provides explanations for failure, allowing the robot to adapt its explanations for more natural and efficient collaboration. Using a dataset…

机器人学 · 计算机科学 2025-04-15 Andreas Naoum , Parag Khanna , Elmira Yadollahi , Mårten Björkman , Christian Smith

As robots increasingly operate in shared, safety critical environments, acting safely is no longer sufficient robots must also make their safety decisions intelligible to human collaborators. In human robot collaboration (HRC), behaviours…

机器人学 · 计算机科学 2026-04-14 Yifan Xu , Xiao Zhan , Akilu Yunusa Kaltungo , Ming Shan Ng , Tsukasa Ishizawa , Kota Fujimoto , Clara Cheung

This study contributes to the evolving field of robot learning in interaction with humans, examining the impact of diverse input modalities on learning outcomes. It introduces the concept of "meta-modalities" which encapsulate additional…

机器人学 · 计算机科学 2024-05-14 Helen Beierling , Anna-Lisa Vollmer

While we do not always use words, communicating what we want to an AI is a conversation -- with ourselves as well as with it, a recurring loop with optional steps depending on the complexity of the situation and our request. Any given…

人机交互 · 计算机科学 2023-09-06 Elena L. Glassman

It is incredibly easy for a system designer to misspecify the objective for an autonomous system ("robot''), thus motivating the desire to have the robot learn the objective from human behavior instead. Recent work has suggested that people…

人工智能 · 计算机科学 2019-07-02 Smitha Milli , Anca D. Dragan

To facilitate human-robot interaction and gain human trust, a robot should recognize and adapt to changes in human behavior. This work documents different human behaviors observed while taking objects from an interactive robot in an…

机器人学 · 计算机科学 2025-01-07 Parag Khanna , Elmira Yadollahi , Iolanda Leite , Mårten Björkman , Christian Smith

Dialogic learning fosters motivation and deeper understanding in education through purposeful and structured dialogues. Foundational models offer a transformative potential for child-robot interactions, enabling the design of personalized,…

人工智能 · 计算机科学 2025-03-21 Elena Malnatsky , Shenghui Wang , Koen V. Hindriks , Mike E. U. Ligthart

Personalisation is essential to achieve more acceptable and effective results in human-robot interaction. Placing users in the central role, many studies have focused on enhancing the abilities of social robots to perceive and understand…

机器人学 · 计算机科学 2023-12-12 Guanyu Huang , Roger K. Moore

Recent years have seen an increasing number of applications that have a natural language interface, either in the form of chatbots or via personal assistants such as Alexa (Amazon), Google Assistant, Siri (Apple), and Cortana (Microsoft).…

计算与语言 · 计算机科学 2022-05-26 Avichai Levy , Erez Karpas

The use of natural language and voice-based interfaces gradu-ally transforms how consumers search, shop, and express their preferences. The current work explores how changes in the syntactical structure of the interaction with…

人工智能 · 计算机科学 2021-11-04 Christian Hildebrand , Donna Hoffman , Tom Novak

As in any interaction process, misunderstandings, ambiguity, and failures to correctly understand the interaction partner are bound to happen in human-robot interaction. We term these failures 'conflicts' and are interested in both conflict…

机器人学 · 计算机科学 2020-01-01 Avinash Kumar Singh , Kai-Florian Richter

People can respond to feedback and guidance in different ways, and it is important for robots to personalize their interactions and utilize verbal and nonverbal communication cues. We aim to understand how older adults respond to different…

机器人学 · 计算机科学 2026-01-14 Roshni Kaushik , Reid Simmons

Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover, a human's unfamiliarity with a robot and its abilities can…

机器人学 · 计算机科学 2023-03-29 Parag Khanna , Elmira Yadollahi , Mårten Björkman , Iolanda Leite , Christian Smith

Integrating generative AI such as Large Language Models into social robots has improved their ability to engage in natural, human-like communication. This study presents a method to examine their persuasive capabilities. We designed an…

机器人学 · 计算机科学 2026-02-10 Stephan Vonschallen , Larissa Julia Corina Finsler , Theresa Schmiedel , Friederike Eyssel

Recent development in developing humanoid robot poses new challenges to human-machine interaction communication. A major challenge is to develop robots that can behave like and interact with human in the most natural way possible. This…

机器人学 · 计算机科学 2014-12-03 Ong Sing Goh , Lance Fung

This paper presents an overview of robot failure detection work from HRI and adjacent fields using failures as an opportunity to examine robot explanation behaviours. As humanoid robots remain experimental tools in the early 2020s,…

人机交互 · 计算机科学 2023-07-11 Dimosthenis Kontogiorgos

We conducted an empirical analysis into the relation between control and discourse structure. We applied control criteria to four dialogues and identified 3 levels of discourse structure. We investigated the mechanism for changing control…

cmp-lg · 计算机科学 2008-02-03 Steve Whittaker , Phil Stenton

Mental models and expectations underlying human-human interaction (HHI) inform human-robot interaction (HRI) with domestic robots. To ease collaborative home tasks by improving domestic robot speech and behaviours for human-robot…

Dialog systems are often designed or trained to output human-like responses. However, some responses may be impossible for a machine to truthfully say (e.g. "that movie made me cry"). Highly anthropomorphic responses might make users…

计算与语言 · 计算机科学 2022-10-25 David Gros , Yu Li , Zhou Yu

Recent years have seen significant market penetration for voice-based personal assistants such as Apple's Siri. However, despite this success, user take-up is frustratingly low. This position paper argues that there is a habitability gap…

人机交互 · 计算机科学 2016-07-19 Roger K. Moore