3D Spatial Collision Detection for Vehicle Interior Configuration
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Solution Overview
Problem
Current interior configuration modeling systems for passenger vehicles, such as airplanes, are manually intensive and struggle to efficiently adjust seat and landmark configurations to meet government and customer requirements, lacking automation and optimal seat placement optimization, leading to inefficiencies and inaccuracies in design.
Innovation Solution
A knowledge-based approach is implemented, using a system that attributes 'hard' and 'soft' spatial volumes to objects, predefining rules for collision resolution, and employing a zonal hierarchy to automate the placement of commodities and spatial areas within the Layout Passenger Accommodations (LOPA) zone, allowing for efficient configuration and compliance with regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration methods are used to place objects in 3D space, then flexibility in configuration is maintained, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary actions by pre-defining spatial volumes (bounding boxes) for all objects before the actual placement process. This allows the configuration system to quickly determine valid placement positions by checking predefined volumes rather than performing complex geometric calculations during manual configuration, thus reducing configuration time while maintaining flexibility
Solution Approach 2:
The patent introduces an intermediary mechanism - the standardized spatial volume (bounding box) - that mediates between the complex 3D geometry of objects and the placement decision-making process. This intermediary representation simplifies collision detection and spatial relationship analysis, enabling faster automated assistance while preserving manual configuration capabilities
2Manufacturing precision
If complex permutation definitions are created to handle all object placement scenarios, then placement accuracy improves, but system complexity increases
Solution Approach 1:
The system changes the parameter representation from complex permutation definitions to simple spatial volume parameters (bounding boxes with position, size, and orientation). This parameter transformation allows the system to handle all placement scenarios by varying these fundamental parameters rather than defining complex permutation rules, reducing system complexity while maintaining placement accuracy
Solution Approach 2:
The patent segments the complex object geometry into simplified bounding box representations. By dividing the complex spatial reasoning task into simpler sub-tasks (checking predefined volumes instead of complex shapes), the system achieves accurate placement decisions without requiring complex permutation definitions
3Manufacturing precision
If automated collision detection is implemented, then placement accuracy improves, but computational resources increase
Solution Approach 1:
The system uses computationally inexpensive bounding box representations instead of detailed 3D models for collision detection. These simplified geometric objects require minimal computational resources to process, allowing accurate automated collision detection without excessive resource consumption. The detailed geometry is only used when actually rendering or manufacturing, not during the placement phase
Data Source
AI summary
A method for resolving collisions for placement of objects in 3D models, including attributing a first state to each object having a hard spatial volume and a second state to each object having a soft spatial volume, predefining a first set of rules to determine whether multiple objects may occupy the same spatial volume based on the combination of the object states, the first set of rules covering all permutations of said first state and said second state, placing a first object in the 3D model, placing a second object in the 3D model, determining whether the first object has a collision with the second object in the 3D model, and resolving the collision based on said first predefined set of rules. Furthermore, there can be predefining a second set of rules that override the first set of rules, and where the resolving of the collision is based on said second set of rules. Further, the method includes finding “soft” and “hard” characters on all objects and defining the characters on all objects.