Teaching Rigid Body Dynamics

This comprehensive video series guides you through leveraging MATLAB to implement a Lagrangian dynamics approach, deriving motion equations for rigid body systems, and automating the process. Delve into the world of computational thinking and its role in mastering rigid body dynamics with MATLAB.

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Over the past few months, we’ve received a lot of questions from our users about rigid body dynamics. We hope this video series will serve as a guide to help you understand how to use MATLAB to implement a Lagrangian dynamics approach for deriving motion equations for rigid body systems.

Part 1: Computational Thinking

This video explores basic concepts of the computational thinking approach and discusses how it can support the teaching of rigid body dynamics.

Part 2: Spring-Mass-Damper System Case Study

In this video, the presenter uses the classic spring-mass-damper system and, through it, demonstrates the workflow of how MATLAB® supports a computational thinking approach.

Part 3: Two-Degrees-of-Freedom Non-Planar Robotic Manipulator Study

Reapplication of the workflow pattern to a larger two-degrees-of-freedom system is the focus of this video

Part 4: Automation

This video outlines the available choices for extending the proposed computational workflow to general multi-degrees-of-freedom systems.

Part 5: Four-Degrees-of-Freedom Non-Planar Robotic Manipulator Study

The final case study is the focus of this video. This case study derives the equations of motion for a four-degrees-of-freedom non-planar robotic manipulator.

Part 6: Summary of Computational Thinking Implementation

This video offers a quick recap of the key features in MATLAB® that support a computational thinking approach when teaching rigid body dynamics.

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