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相关概念视频

Stereotype Content Model02:16

Stereotype Content Model

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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...
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SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
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Schemas01:42

Schemas

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A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
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Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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State Space Representation01:27

State Space Representation

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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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相关实验视频

Updated: Jan 9, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

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在移动机器人部署期间基于语义的情境意识的框架.

Tianshu Ruan1, Aniketh Ramesh1, Hao Wang1

  • 1Extreme Robotics Lab (ERL) and National Center for Nuclear Robotics (NCNR), University of Birmingham, Birmingham, United Kingdom.

Frontiers in robotics and AI
|December 5, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一个机器人理解危险任务期间复杂环境的框架. 它使用语义指标和情境语义丰富度指标来增强人机组合和情境意识,以便更好地做出决策.

关键词:
灾难应对机器人机器人技术人类-机器人合作.搜索和救援机器人机器人技术语义上的理解 语义上的理解语义学的语义学情境意识:情况意识.

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SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
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SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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相关实验视频

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科学领域:

  • 机器人和人工智能 机器人和人工智能
  • 人与机器人的交互
  • 应对灾害的技术 应对灾害的技术

背景情况:

  • 人机组合 (HRT) 对危险环境至关重要,需要强大的情境意识 (SA).
  • 现有的SA框架往往忽视了对半自主系统至关重要的更高层次的语义理解.
  • 有效的HRT依赖于人类操作员和自主代理人处理复杂的环境信息.

研究的目的:

  • 为移动机器人在远程部署中获取和集成多模式语义SA提出一个可通用的框架.
  • 开发"环境语义指标"和"情境语义丰富性" (SSR) 度量来评估环境复杂性.
  • 在像搜救 (SAR) 这样的关键场景中增强决策和操作员注意力.

主要方法:

  • 为机器人SA.开发了一个框架,将多种语义信息模式结合起来.
  • 引入了用于现场分析的"环境语义指标" (例如风险,人类活动的迹象).
  • 提出了"情境语义丰富性" (SSR) 度量来量化整体环境复杂性.

主要成果:

  • 提出的语义指标有效地捕获了不同场景中的多样化语义信息.
  • SSR指标准确地反映了整体语义变化,表明了信息丰富的情况.
  • 在模拟灾难环境中对Jackal机器人进行实验验证,证实了框架的敏感性.

结论:

  • 开发的框架增强了在危险环境中移动机器人的语义SA.
  • SSR指标为评估情况的复杂性和指导操作员干预提供了有价值的工具.
  • 这种方法提高了人机组合在灾难响应等关键应用中的有效性.