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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

Humanoid robots are designed to be relatable to humans for applications such as customer support and helpdesk services. However, many such systems, including Softbank's Pepper, fall short because they fail to communicate effectively with…

机器人学 · 计算机科学 2024-02-13 Xiaohui Chen , Katherine Luo , Trevor Gee , Mahla Nejati

How should a robot speak in a formal, quiet and dark, or a bright, lively and noisy environment? By designing robots to speak in a more social and ambient-appropriate manner we can improve perceived awareness and intelligence for these…

机器人学 · 计算机科学 2025-05-01 Paige Tuttosi , Emma Hughson , Akihiro Matsufuji , Angelica Lim

Service and assistive robots are increasingly being deployed in dynamic social environments; however, ensuring transparent and explainable interactions remains a significant challenge. This paper presents a multimodal explainability module…

机器人学 · 计算机科学 2026-04-09 Oluwadamilola Sotomi , Devika Kodi , Aliasghar Arab

Is it possible to integrate a humanoid social robot into the work processes or customer care in an official environment, e.g. in municipal offices? If so, what could such an application scenario look like and what skills would the robot…

机器人学 · 计算机科学 2024-12-09 Thomas Sievers , Nele Russwinkel

Spoken language interaction is at the heart of interpersonal communication, and people flexibly adapt their speech to different individuals and environments. It is surprising that robots, and by extension other digital devices, are not…

机器人学 · 计算机科学 2024-05-17 Qiaoqiao Ren , Yuanbo Hou , Dick Botteldooren , Tony Belpaeme

The addressee estimation (understanding to whom somebody is talking) is a fundamental task for human activity recognition in multi-party conversation scenarios. Specifically, in the field of human-robot interaction, it becomes even more…

The rise of connectivity, digitalization, robotics, and artificial intelligence (AI) is rapidly changing our society and shaping its future development. During this technological and societal revolution, security has been persistently…

密码学与安全 · 计算机科学 2018-07-06 Alberto Giaretta , Michele De Donno , Nicola Dragoni

There is a need for socially assistive robots (SARs) to provide transparency in their behavior by explaining their reasoning. Additionally, the reasoning and explanation should represent the user's preferences and goals. To work towards…

机器人学 · 计算机科学 2020-12-08 Jason R. Wilson , Leilani Gilpin , Irina Rabkina

Although innovation and the support of new technologies are much needed to ease the burden on the education system, social robots in schools to help teachers with educational tasks are rare. Child-Robot Interaction (CRI) could support…

人机交互 · 计算机科学 2025-08-11 Thomas Sievers

Service robots need to show appropriate social behaviour in order to be deployed in social environments such as healthcare, education, retail, etc. Some of the main capabilities that robots should have are navigation and conversational…

机器人学 · 计算机科学 2018-11-15 Chandrakant Bothe , Fernando Garcia , Arturo Cruz Maya , Amit Kumar Pandey , Stefan Wermter

The current spread of social and assistive robotics applications is increasingly highlighting the need for robots that can be easily taught and interacted with, even by users with no technical background. Still, it is often difficult to…

With growing societal acceptance and increasing cost efficiency due to mass production, service robots are beginning to cross from the industrial to the social domain. Currently, customer service robots tend to be digital and emulate social…

人机交互 · 计算机科学 2022-06-02 Jordan J. Bird

Robots often need to convey information to human users. For example, robots can leverage visual, auditory, and haptic interfaces to display their intent or express their internal state. In some scenarios there are socially agreed upon…

机器人学 · 计算机科学 2024-09-17 Benjamin A. Christie , Heramb Nemlekar , Dylan P. Losey

In this paper we present our work with the Pepper robot, a service robot from SoftBank Robotics. We had two main goals in this work: improving the autonomy of this robot by increasing its awareness of the environment; and enhance the robot…

机器人学 · 计算机科学 2017-04-18 Vittorio Perera , Tiago Pereira , Jonathan Connell , Manuela Veloso

Explanations constitute an important aspect of successful human robot interactions and can enhance robot understanding. To improve the understanding of the robot, we have developed four levels of explanation (LOE) based on two questions:…

机器人学 · 计算机科学 2025-01-22 Shikhar Kumar , Yael Edan

Social robots are increasingly experimented in public and assistive settings, but their accessibility for Deaf users remains quite underexplored. Italian Sign Language (LIS) is a fully-fledged natural language that relies on complex manual…

机器人学 · 计算机科学 2025-09-15 Giulia Botta , Marco Botta , Cristina Gena , Alessandro Mazzei , Massimo Donini , Alberto Lillo

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

Artificial Intelligence (AI) has significantly advanced in recent years, driving innovation across various fields, especially in robotics. Even though robots can perform complex tasks with increasing autonomy, challenges remain in ensuring…

人机交互 · 计算机科学 2025-03-24 Anargh Viswanath , Lokesh Veeramacheneni , Hendrik Buschmeier

This paper explores the challenges faced by assistive robots in effectively cooperating with humans, requiring them to anticipate human behavior, predict their actions' impact, and generate understandable robot actions. The study focuses on…

机器人学 · 计算机科学 2023-08-22 Chao Wang , Theodoros Stouraitis , Anna Belardinelli , Stephan Hasler , Michael Gienger
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