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Stereotype Content Model02:16

Stereotype Content Model

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 categorization, a person will feel...
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...

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Related Experiment Video

Updated: Jul 7, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

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

Published on: October 14, 2017

Sensor explication: knowledge-based robotic plan execution through logical objects.

J Budenske1, M Gini

  • 1Dept. of Comput. Sci., Minnesota Univ., Minneapolis, MN.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|January 1, 1997
PubMed
Summary
This summary is machine-generated.

This study introduces a sensor explication concept for robots, transforming high-level goals into executable commands. This approach enhances robot task robustness by making crucial details explicit during plan execution.

Related Experiment Videos

Last Updated: Jul 7, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

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

Published on: October 14, 2017

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Sensor Fusion

Background:

  • Complex robot tasks require detailed command generation from high-level goals.
  • Current methods lack explicit detail for real-time robot control.

Purpose of the Study:

  • To present a sensor explication concept for making task details explicit.
  • To enable real-time transformation of high-level goals into primitive robot commands.

Main Methods:

  • Developed a reconfigurable object architecture storing domain and sensor/actuator knowledge.
  • Implemented plan execution as an information-gathering process.
  • Utilized sonic range data for navigation through unknown doorways.

Main Results:

  • Demonstrated successful robot navigation through unknown doorways.
  • Showcased the transformation of high-level goals to primitive commands at execution time.
  • Validated the approach through extensive real-world mobile robot experiments.

Conclusions:

  • Explicitly detailing information is crucial for robust plan execution.
  • Integrating and utilizing sensor and actuator knowledge enhances robot task performance.