AI Locomotion Animation Generation With Foot Contact Synchronization
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Solution Overview
Problem
Existing methods for creating character locomotion animations in 3D games, such as motion capture and manual keyframe animation, are resource-intensive, costly, and lack flexibility, leading to inefficient and less customizable animations, often relying on pre-made sets that compromise game originality.
Innovation Solution
An AI-assisted system using diffusion models and ControlNet to generate high-quality, synchronized, and loopable locomotion animations from minimal user inputs, integrating seamlessly into game development workflows and allowing real-time customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If motion capture is used to create realistic character animations, then animation realism is improved, but cost and post-processing requirements increase significantly
Solution Approach 1:
The patent replaces the mechanical motion capture system with an AI-based generative model that synthesizes locomotion animations programmatically. The system uses a trained neural network model to generate synchronized foot contact animations directly from input parameters, eliminating the need for physical capture equipment and subsequent mechanical post-processing alignment operations.
Solution Approach 2:
The AI model performs self-synchronization of animation clips by automatically generating coordinated foot contact patterns for multiple directions and speeds. The system independently handles the synchronization task that would otherwise require manual post-processing, making the animation generation process self-sufficient and reducing external intervention requirements.
2Adaptability or versatility
If manual keyframe animation is used to create flexible and customizable animations, then animation customization is improved, but time and expertise requirements increase significantly
Solution Approach 1:
The system creates master animation templates for each movement type (walking, running, etc.) that are stored and reused. When generating animations for different directions or speeds, the system copies and transforms these base templates rather than creating animations from scratch, dramatically reducing the time and expertise required while maintaining full customization capability.
Solution Approach 2:
The patent implements a parameter-driven animation system where changing numerical parameters (direction angles, speed values, duration) automatically transforms the base animation templates. This allows extensive customization without manual intervention, as the AI model generates variations by interpolating between parameter states rather than requiring manual keyframe adjustment for each variation.
3Productivity
If pre-made animation sets are used to reduce development cost and time, then development cost is reduced, but game originality and customization are compromised
Solution Approach 1:
The AI model serves multiple functions: it generates animations for any direction, speed, and movement type requested by the developer. A single system replaces the need for multiple pre-made animation sets, providing universal animation generation capability that adapts to any game scenario while maintaining originality through AI-synthesized content rather than reused assets.
4Reliability
If traditional animation methods are used to ensure smooth gameplay transitions, then transition quality is improved, but development complexity increases significantly
Solution Approach 1:
The system pre-calculates and pre-synchronizes foot contact patterns for all required directions and speeds during the animation generation phase. By performing this synchronization work in advance rather than during gameplay, the system ensures smooth transitions are built into the animation data structure itself, eliminating the need for complex runtime synchronization logic and reducing overall system complexity.
Data Source
AI summary
A method of generating a locomotion set for a character is disclosed. One or more text inputs specifying movement style and base locomotion speed are received. A forward motion clip is generated using a first model. The first model transforms a noisy sequence into a denoised, prompt-following motion with predicted foot contact states. The forward motion clip is extended to one or more additional motion clips via a second model. The second model synchronizes the one or more additional motion clips to cover multiple directions based on the one or more text inputs. The locomotion set is adjusted based on one or more user interactions.


