Collision Detection via Rigid Body Binding and Model Cutting
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Solution Overview
Problem
Current collision simulation methods in computer technology require constructing models from multiple independent models, leading to increased computation load and reduced efficiency due to the need for multiple collision detections, resulting in labor-intensive model building and decreased simulation fluency.
Innovation Solution
A method where a physical engine determines an initial cutting model from two independent original models based on their physical attributes, captures collision points, and determines normal vector information to simulate collisions, reducing the number of collision detections and improving simulation efficiency by directly performing collision detection on bound rigid bodies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If models are constructed from multiple independent models, then collision detection accuracy is improved, but computation load increases and efficiency decreases
Solution Approach 1:
The patent segments the collision detection process into two stages: first performs collision detection on the bound rigid bodies (coarse detection), then performs detailed collision detection on the independent models only when collision is detected (fine detection). This segmentation reduces unnecessary computations while maintaining accuracy.
Solution Approach 2:
The patent binds rigid bodies to models in advance as a preliminary action. This rigid body binding serves as a pre-filter that quickly identifies potential collisions before detailed model-level detection is performed, reducing the overall computation load.
2Measurement precision
If multiple independent models are used for collision detection, then collision detection accuracy is improved, but labor cost increases due to manual model fragmentation
Solution Approach 1:
The system performs automatic rigid body binding and automatic model fragmentation without requiring manual intervention. The computer automatically generates the independent models and binds rigid bodies to them, eliminating the need for manual model fragmentation while maintaining collision detection accuracy.
3Productivity
If rigid bodies are bound to models, then collision detection efficiency is improved, but device complexity increases
Solution Approach 1:
The rigid body serves multiple functions: it acts as both a collision detection object and a reference for model fragmentation. This multi-functionality reduces the need for separate systems while maintaining efficiency.
Data Source
AI summary
A collision data processing method includes: determining, based on a physical engine detecting that a first rigid body having a first physical attribute collides with a second rigid body having a second physical attribute, an initial cutting model from a first model corresponding to the first rigid body and a second model corresponding to the second rigid body based on the first physical attribute and the second physical attribute, capturing, by the physical engine, a collision point between the first rigid body and the second rigid body, and determining normal vector information corresponding to the collision point based on collision data, and determining a first cutting surface in the initial cutting model based on the collision point, the normal vector information, and model information of the initial cutting model, and cutting the initial cutting model based on the first cutting surface to obtain cutting data.