Complete Binary Tree Shuffling for Collision Detection
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Solution Overview
Problem
Conventional methods for constructing binary trees to facilitate collision determination in virtual simulations are inefficient due to uneven object distributions across layers, hindering parallel processing as the number of objects increases.
Innovation Solution
A simulation device and method that creates a complete binary tree by associating position information with leaves and internal nodes, and shuffles child nodes to optimize regional overlap, enabling efficient collision determination through parallel processing across layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional binary tree construction method is used, then collision determination can be performed, but processing load increases enormously as number of objects increases
Solution Approach 1:
The patent divides the virtual space into multiple regions using a binary tree structure, where each node represents a region containing a subset of objects. This segmentation allows the collision determination system to process objects in hierarchical groups rather than individually, reducing the overall processing load while maintaining comprehensive collision detection capability.
Solution Approach 2:
The patent introduces a spatial hierarchy dimension by organizing objects into a binary tree structure with multiple layers. Instead of processing objects in a single flat list, the system processes them through hierarchical levels (root, children, grandchildren, etc.), adding a dimensional structure that enables more efficient collision determination by skipping non-overlapping regions.
2Productivity
If binary tree construction is performed to reduce collision determination times, then collision detection efficiency improves, but parallel processing becomes inefficient due to uneven object distributions across layers
Solution Approach 1:
The patent applies local quality by ensuring that each region (node) in the binary tree contains a balanced and uniform distribution of objects. This is achieved by carefully constructing the tree so that sibling nodes have comparable numbers of objects, creating locally optimized structures that are suitable for parallel processing. Each region becomes a self-contained unit with homogeneous object density, enabling efficient parallel execution.
Solution Approach 2:
The patent changes the structural parameters of the binary tree by adjusting the assignment of objects to nodes to achieve balanced object distributions across all layers. By modifying the tree construction parameters (such as region division criteria and object assignment rules), the system creates a tree structure that optimizes both collision determination efficiency and parallel processing performance.
3Ease of operation
If complete binary tree with balanced node distribution is created, then parallel processing efficiency improves, but tree construction complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-dividing the virtual space into a complete binary tree structure before performing collision determination. The tree is constructed in advance with balanced object distributions, creating a ready-to-use hierarchical framework that simplifies subsequent parallel processing operations. This preliminary structuring eliminates the need for complex dynamic adjustments during execution.
Solution Approach 2:
The patent changes the construction parameters to create a complete binary tree with uniform object distribution. By using specific division criteria and assignment rules, the system achieves balanced node populations without requiring overly complex algorithms. The parameter adjustments enable straightforward tree construction while ensuring optimal properties for parallel processing.
Data Source
AI summary
Methods and apparatus provide for, at each of plural calculation timings, associating pieces of position information indicating the positions of objects in a virtual space at the calculation timing with leaves and creates a complete binary tree in which position information reflecting pieces of the position information of child nodes is associated with an internal node, and a node shuffling section that shuffles 2·2n (n≥1) child nodes regarding each group of 2n nodes on the basis of the position information associated with each of the 2·2n child nodes belonging to the 2n nodes in each layer sequentially from the immediately-upper layer of the lowermost layer in the complete binary tree; and carrying out collision determination between objects by using the complete binary tree resulting from the shuffling by the node shuffling section.