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Related Concept Videos

Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
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Kinematic Equations for Rotation01:30

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In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
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The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
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When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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Kinematic Equations - II01:17

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The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
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Kinematic Equations - I01:26

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When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
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Related Experiment Video

Updated: Aug 21, 2025

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
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A Geometric Kinematic Model for Flexible Voxel-Based Robots.

Maryam Tebyani1, Alex Spaeth1,2, Nicholas Cramer3

  • 1Department of Electrical and Computer Engineering, University of California, Santa Cruz, Santa Cruz, California, USA.

Soft Robotics
|November 16, 2022
PubMed
Summary

This study introduces a new kinematic model for voxel-based soft robots, enabling precise control through internal deformations. The model accurately predicts robot motion for tasks like locomotion and grasping.

Keywords:
flexible locomotionkinematic modelingmodular robots

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Area of Science:

  • Robotics
  • Materials Science
  • Mechanical Engineering

Background:

  • Voxel-based structures offer modularity and mechanical flexibility for soft robotics.
  • Internal deformations enable soft robots to perform various tasks.
  • Characterizing motion in these structures is crucial for robotic applications.

Purpose of the Study:

  • To develop a reduced kinematic model for voxel-based periodic lattices.
  • To enable user-defined control and end-effector node manipulation.
  • To demonstrate the model's utility in designing robotic grippers and locomotors.

Main Methods:

  • Utilized finite element analysis to characterize motion from single degree-of-freedom deformations.
  • Developed a reduced kinematic model based on observed node movement patterns.
  • Validated the quasi-static model with physical experiments for a locomotive robot.

Main Results:

  • Identified that lattice nodes move along specific geometric planes, primarily translational degrees of freedom.
  • The derived 'Planes of Motion' model effectively handles both forward and inverse kinematics.
  • Successfully designed and demonstrated a voxel-based robotic gripper and locomotor.

Conclusions:

  • The developed kinematic model provides a powerful framework for controlling voxel-based soft robots.
  • The 'Planes of Motion' model simplifies complex structural deformations for robotic tasks.
  • This approach facilitates the design of sophisticated soft robotic systems with validated performance.