Soft Body Locomotion Controller Pipeline for Virtual Environments
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Solution Overview
Problem
Existing technologies face challenges in efficiently animating soft bodies in three-dimensional virtual environments due to the high dimensionality of deformable object simulations, which makes the process slow and difficult to control.
Innovation Solution
The implementation of a scalable soft body controller pipeline that uses a control space with information representing natural movement forces of the soft body, coupled with a physical space to define an efficient animation controller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional physics-based character controller pipelines are used for rigid characters, then the controller design is straightforward, but the morphology of the character and controller style are limited
Solution Approach 1:
The patent segments the character controller into two independent parts: a rigid body controller that handles locomotion and a soft body simulator that handles deformation. This segmentation allows the controller to work with various soft body morphologies without redesigning the entire control pipeline, thus improving adaptability while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces a soft body simulator as an intermediary component between the rigid body controller and the visual representation of the character. This intermediary handles the complex deformation calculations and couples the rigid controller with soft body physics, enabling versatile morphology support without complicating the core control logic.
2Manufacturing precision
If deformable object simulations are performed with high dimensionality, then the soft body deformation is accurate, but the simulation process becomes prohibitively slow
Solution Approach 1:
The patent segments the deformation simulation into a reduced-dimensional control space and a physical space. By projecting the high-dimensional soft body deformation problem into a lower-dimensional control space parameterized by a few coefficients, the system maintains accurate deformation representation while dramatically reducing computational complexity and increasing simulation speed.
Solution Approach 2:
The patent changes the parameter representation from full high-dimensional vertex positions to a small set of control coefficients that define the deformation mode. This parameter transformation allows the system to achieve the same visual accuracy with much fewer degrees of freedom, resolving the contradiction between accuracy and speed.
3Adaptability or versatility
If high dimensionality problems are solved directly, then the soft body simulation is comprehensive, but the control becomes difficult
Solution Approach 1:
The patent transforms the control problem from high-dimensional vertex space to a low-dimensional control coefficient space. By changing the dimensionality of the control parameters, the system maintains comprehensive soft body movement representation while making control intuitive and manageable through a reduced parameter space that can be easily manipulated.
Data Source
AI summary
Some implementations relate to methods, systems, and computer-readable media to provide scalable soft body locomotion/animation for a virtual experience, such as a three-dimensional (3D) environment. In some implementations, the method includes building a control space having information representative of forces corresponding to natural movement of the soft body, wherein the soft body is part of a virtual environment, coupling the control space and a physical space to define a controller pipeline that performs animation of the soft body, performing the animation of the soft body using the controller pipeline, and causing the animation of the soft body to be displayed in a user interface of the virtual environment. Building the control space may comprise simulating the forces corresponding to the natural movement of the soft body by solving an elastodynamic optimization problem using auxiliary variables as degrees of freedom.