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相关论文: User, Robot, Deployer: A New Model for Measuring T…

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Since trust measures in human-robot interaction are often subjective or not possible to implement real-time, we propose to use speech cues (on what, when and how the user talks) as an objective real-time measure of trust. This could be…

人机交互 · 计算机科学 2021-04-13 Ella Velner , Khiet P. Truong , Vanessa Evers

Recent advances in learning-based robot manipulation have produced policies with remarkable capabilities. Yet, reliability at deployment remains a fundamental barrier to real-world use, where distribution shift, compounding errors, and…

机器人学 · 计算机科学 2026-03-13 Christopher Agia

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

When interacting with each other, humans adjust their behavior based on perceived trust. To achieve similar adaptability, robots must accurately estimate human trust at sufficiently granular timescales while collaborating with humans. Beta…

机器人学 · 计算机科学 2025-07-18 Resul Dagdanov , Milan Andrejevic , Dikai Liu , Chin-Teng Lin

Advances in the control of autonomous systems have accompanied an expansion in the potential applications for autonomous robotic systems. The success of applications involving humans depends on the quality of interaction between the…

机器人学 · 计算机科学 2025-10-13 Daniel A. Williams , Airlie Chapman , Daniel R. Little , Chris Manzie

Trust in robots has been gathering attention from multiple directions, as it has special relevance in the theoretical descriptions of human-robot interactions. It is essential for reaching high acceptance and usage rates of robotic…

机器人学 · 计算机科学 2021-06-07 Hebert Azevedo-Sa , X. Jessie Yang , Lionel P. Robert , Dawn M. Tilbury

In this paper, we present a framework for trust-aware sequential decision-making in a human-robot team. We model the problem as a finite-horizon Markov Decision Process with a reward-based performance metric, allowing the robotic agent to…

机器人学 · 计算机科学 2022-06-06 Shreyas Bhat , Joseph B. Lyons , Cong Shi , X. Jessie Yang

A significant challenge to measuring human-automation trust is the amount of construct proliferation, models, and questionnaires with highly variable validation. However, all agree that trust is a crucial element of technological…

人机交互 · 计算机科学 2023-03-27 Yosef S. Razin , Karen M. Feigh

In human-robot collaboration (HRC), human trust in the robot is the human expectation that a robot executes tasks with desired performance. A higher-level trust increases the willingness of a human operator to assign tasks, share plans, and…

机器人学 · 计算机科学 2021-06-30 Ruijiao Luo , Chao Huang , Yuntao Peng , Boyi Song , Rui Liu

Humans are constantly influenced by others' behavior and opinions. Of importance, social influence among humans is shaped by reciprocity: we follow more the advice of someone who has been taking into consideration our opinions. In the…

机器人学 · 计算机科学 2022-06-17 Joshua Zonca , Anna Folso , Alessandra Sciutti

Trust plays a central role in human--robot collaboration, yet its formation is rarely examined under the constraints of fully autonomous interaction. This pilot study investigated how interaction policy influences trust during in-person…

机器人学 · 计算机科学 2026-03-18 Shauna Heron , Meng Cheng Lau

For humans and robots to form an effective human-robot team (HRT) there must be sufficient trust between team members throughout a mission. We analyze data from an HRT experiment focused on trust dynamics in teams of one human and two…

This paper surveys the area of Trust Metrics related to security for autonomous robotic systems. As the robotics industry undergoes a transformation from programmed, task oriented, systems to Artificial Intelligence-enabled learning, these…

机器人学 · 计算机科学 2023-04-05 Vincenzo DiLuoffo , William R. Michalson

As the use of Augmented Reality (AR) to enhance interactions between human agents and robotic systems in a work environment continues to grow, robots must communicate their intents in informative yet straightforward ways. This improves the…

机器人学 · 计算机科学 2023-03-13 Chrisantus Eze , Christopher Crick

Human-robot interactions (HRI) can be modeled as dynamic or differential games with incomplete information, where each agent holds private reward parameters. Due to the open challenge in finding perfect Bayesian equilibria of such games,…

机器人学 · 计算机科学 2020-11-05 Yi Chen , Lei Zhang , Tanner Merry , Sunny Amatya , Wenlong Zhang , Yi Ren

Nowadays, robots are expected to interact more physically, cognitively, and socially with people. They should adapt to unpredictable contexts alongside individuals with various behaviours. For this reason, personalisation is a valuable…

Increasing anthropomorphic robot behavioral design could affect trust and cooperation positively. However, studies have shown contradicting results and suggest a task-dependent relationship between robots that display emotions and trust.…

The Trust, Acceptance and Social Cues in Human-Robot Interaction - SCRITA is the 5th edition of a series of workshops held in conjunction with the IEEE RO-MAN conference. This workshop focuses on addressing the challenges and development of…

机器人学 · 计算机科学 2022-08-30 Alessandra Rossi , Patrick Holthaus , Sìlvia Moros , Gabriella Lakatos

As robotic teammates become more common in society, people will assess the robots' roles in their interactions along many dimensions. One such dimension is effectiveness: people will ask whether their robotic partners are trustworthy and…

人工智能 · 计算机科学 2020-10-13 Richard G. Freedman , Steven J. Levine , Brian C. Williams , Shlomo Zilberstein

Human trust plays a crucial role in the effectiveness of human-robot collaboration. Despite its significance, the development and maintenance of an optimal trust level are obstructed by the complex nature of influencing factors and their…

机器人学 · 计算机科学 2024-12-31 Hao Guo , Bangan Wu , Qi Li , Zhen Ding , Feng Jiang , Chunzhi Yi