Nvidia corporation (20240161377). PHYSICS-BASED SIMULATION OF HUMAN CHARACTERS IN MOTION simplified abstract

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PHYSICS-BASED SIMULATION OF HUMAN CHARACTERS IN MOTION

Organization Name

nvidia corporation

Inventor(s)

Zhengyi Luo of Pittsburgh PA (US)

Jason Peng of Vancouver (CA)

Sanja Fidler of Toronto (CA)

Or Litany of Sunnyvale CA (US)

Davis Winston Rempe of Redwood City CA (US)

Ye Yuan of Santa Clara CA (US)

PHYSICS-BASED SIMULATION OF HUMAN CHARACTERS IN MOTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240161377 titled 'PHYSICS-BASED SIMULATION OF HUMAN CHARACTERS IN MOTION

Simplified Explanation

The patent application describes a system for generating a simulated environment and updating a machine learning model to control the movement of human characters with different body shapes within the environment.

  • The system uses a machine learning model to determine actions for human characters based on their body shape and task-related features.
  • The simulated human characters in the environment have diverse characteristics like gender, body proportions, and body shape, similar to real-life crowds.
  • The machine learning model considers humanoid state, body shape, and task-related features like environmental features and trajectories to control the movement of human characters.

Potential Applications

This technology could be applied in:

  • Virtual reality gaming
  • Crowd simulation for urban planning and safety analysis

Problems Solved

This technology helps in:

  • Creating realistic simulations of human movement in various scenarios
  • Improving the accuracy of crowd behavior predictions

Benefits

The benefits of this technology include:

  • Enhanced user experience in virtual environments
  • Better understanding of crowd dynamics for real-world applications

Potential Commercial Applications

The technology could be used in:

  • Entertainment industry for creating immersive experiences
  • Urban planning for simulating crowd behavior in public spaces

Possible Prior Art

One possible prior art could be existing crowd simulation software used in urban planning and emergency response training.

What is the impact of this technology on virtual reality gaming experiences?

This technology can significantly enhance the realism and immersion of virtual reality gaming experiences by creating more lifelike and dynamic human character movements within the simulated environments.

How does this technology improve safety analysis in urban planning?

By accurately simulating crowd behavior based on diverse body shapes and characteristics, this technology can provide valuable insights for urban planners to optimize public spaces for safety and efficiency.


Original Abstract Submitted

in various examples, systems and methods are disclosed relating to generating a simulated environment and update a machine learning model to move each of a plurality of human characters having a plurality of body shapes, to follow a corresponding trajectory within the simulated environment as conditioned on a respective body shape. the simulated human characters can have diverse characteristics (such as gender, body proportions, body shape, and so on) as observed in real-life crowds. a machine learning model can determine an action for a human character in a simulated environment, based at least on a humanoid state, a body shape, and task-related features. the task-related features can include an environmental feature and a trajectory.