Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Improving Translational Accuracy02:07

Improving Translational Accuracy

2.5K
2.5K
Stereotype Content Model02:16

Stereotype Content Model

14.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

100 Normative Gait Profiles with 5-year fall tracking: Benchmark Dataset for Southeast Asian Movement Science.

Scientific data·2026
Same author

Prediction for prospective falls via gait evaluation using mobile devices for stroke survivors: A markerless motion analysis study.

Clinical rehabilitation·2026
Same author

Simulating Safe Bite Transfer in Robot-Assisted Feeding with a Soft Head and Articulated Jaw.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same author

Design and Evaluation of a Single-Sided Mobility Assistive Exoskeleton (SMAEXO) for Hemiplegia.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same author

Muscle Activation and Postural Sway in Response to Task Complexity: A Study of Balance Control in Older Adults.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same author

Design of a Breakaway Utensil Attachment for Enhanced Safety in Robot-Assisted Feeding.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same journal

Passive wheels on legged robots: a survey.

Frontiers in robotics and AI·2026
Same journal

Politeness cannot make up for robots' errors.

Frontiers in robotics and AI·2026
Same journal

Workers expect basic social skills but limited autonomy from future robots - a qualitative interview study and taxonomy for robot social skills.

Frontiers in robotics and AI·2026
Same journal

Human-robot interaction in sustainable hospitality: how robot type shapes customer emotions, green perceptions, and service loyalty.

Frontiers in robotics and AI·2026
Same journal

Dynamic variance-aware federated tuning for efficient autonomous vehicle perception under non-IID settings.

Frontiers in robotics and AI·2026
Same journal

Editorial: Synergizing large language models and computational intelligence for advanced robotic systems.

Frontiers in robotics and AI·2026
查看所有相关文章

相关实验视频

Updated: Jun 11, 2025

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

13.8K

ExTraCT - 基于语言的人机交互的可解释轨迹纠正,使用文本特征描述.

J-Anne Yow1,2, Neha Priyadarshini Garg1, Manoj Ramanathan1

  • 1Rehabilitation Research Institute of Singapore (RRIS), Joint Research Institute by Nanyang Technological University (NTU), Agency for Science, Technology and Research (A∗STAR) and National Healthcare Group (NHG), Singapore, Singapore.

Frontiers in robotics and AI
|October 8, 2024
PubMed
概括
此摘要是机器生成的。

一个新的框架ExTraCT通过使用自然语言修改机器人路径来增强人机交互. 这种方法更准确,用户更喜欢,改善了机器人任务与人类偏好的调整.

关键词:
有助于机器人的机器人基础模型 基础模型人与机器人的交互机器人技术中的语言大型语言模型.自然语言处理自然语言处理.

更多相关视频

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

9.9K
Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
07:36

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

Published on: November 30, 2018

15.7K

相关实验视频

Last Updated: Jun 11, 2025

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

13.8K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

9.9K
Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
07:36

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

Published on: November 30, 2018

15.7K

科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人与机器人的交互
  • 人工智能的人工智能

背景情况:

  • 了解人类的意图对于机器人来说至关重要,以便在人机交互 (HRI) 中将任务与用户偏好保持一致.
  • 基于语言纠正的传统轨迹修改方法需要广泛的培训,并难以在各种场景中进行概括.
  • 现有的方法往往依赖于端到端的学习,限制了适应性,需要大量的预训练数据集.

研究的目的:

  • 介绍ExTraCT,一个模块化框架,用于修改使用自然语言输入的机器人轨迹和行为.
  • 让机器人能够将语言纠正适应新任务,包括复杂的动作,而无需额外的端到端训练.
  • 为HRI应用提供更易于解释和多功能解决方案.

主要方法:

  • ExTraCT将语言理解与轨迹修改分开,使用大型语言模型 (LLM) 进行语义匹配.
  • 该框架将语言纠正映射到预定义的轨迹修改函数,用于机器人路径调整.
  • 模块化设计允许适应各种对象,初始轨迹和配置.

主要成果:

  • 模拟和使用物理机器人手臂的用户研究表明,ExTraCT校正在80%的病例中是首选的.
  • 该系统的准确性比基线方法有所改善.
  • 在复杂的场景中,如辅助养,ExTraCT证明是有效的.

结论:

  • ExTraCT提供了一种多功能且易于解释的方法来解释HRI中的语言纠正.
  • 模块化框架克服了传统方法的局限性,在各种应用中提供了适应性.
  • 这项技术有助于机器人学习人类的偏好,并改善任务对齐.