Physical 3D Renderer Sliding Shaft Array Depth Mapping
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Solution Overview
Problem
Current 3D rendering technologies do not effectively create accurate, real-time physical 3D surfaces that mimic complex objects, especially when requiring high resolution and dynamic updates, which limits their application in fields like telepresence and training.
Innovation Solution
A computer-implemented process using a physical 3D renderer that captures depth images and adjusts an array of sliding shafts or air jets to recreate the surface, with verification through secondary depth cameras to ensure accuracy, allowing for real-time updates and high-resolution rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional 3D rendering technologies are used, then the rendering process is simple, but the accuracy and realism of physical 3D surfaces are insufficient
Solution Approach 1:
The rendering system divides the surface into discrete depth points arranged in a grid pattern, with each point independently controlled by individual actuators. This segmentation allows precise control of each surface element to match the target depth image while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The system dynamically adjusts the depth parameter of each surface point based on real-time depth image data. By changing the z-position parameter of each actuator to match corresponding depth values from the target object, the system achieves high manufacturing precision of physical 3D surfaces
2Manufacturing precision
If high resolution depth mapping is implemented, then the surface accuracy improves, but the processing time and computational load increase
Solution Approach 1:
The system pre-establishes a grid pattern of depth points across the rendering surface before processing. This preliminary arrangement of points in systematic rows and columns allows for efficient mapping of depth data without requiring complex real-time calculations during operation
Solution Approach 2:
The system replaces complex mechanical measurement systems with optical depth sensing technology. Depth cameras or sensors directly capture the target object's surface depth information, eliminating the need for manual measurement or complex mechanical scanning while achieving high surface accuracy
3Speed
If real-time updates are enabled, then the system responsiveness improves, but the computational requirements and energy consumption increase
Solution Approach 1:
The system updates the physical 3D surface at periodic intervals by comparing successive depth images. Rather than continuously adjusting all actuators, the system periodically refreshes the surface representation, allowing actuators to remain stationary between updates and reducing overall energy consumption while maintaining real-time responsiveness
Solution Approach 2:
The system dynamically adjusts only those actuators whose depth values have changed between frames, rather than continuously actuating all elements. This dynamic approach enables fast response to changes in the target object while minimizing unnecessary actuator movement and energy consumption
4Measurement precision
If verification through secondary depth cameras is implemented, then the accuracy verification improves, but the device complexity and cost increase
Solution Approach 1:
Secondary depth cameras capture images of the rendered physical surface and feed this information back to the control system. The control system compares the rendered surface depth with the target depth image, using this feedback to verify accuracy and make corrective adjustments to actuators for improved precision
Solution Approach 2:
The secondary depth cameras serve multiple functions: they verify the accuracy of rendered surfaces, provide feedback for correction, and can detect errors in the rendering process. This multi-functionality justifies the additional device complexity by providing comprehensive verification capabilities
Data Source
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AI summary
The physical 3D renderer described herein renders one or more captured depth images as a physical 3D rendering. The physical 3D renderer can render physical 3D surfaces and structures in real time. In one embodiment the 3D renderer creates a physical three dimensional (3D) topological surface from captured images. To this end, a depth image of a surface or structure to be replicated is received (for example from a depth camera or depth sensor). Depth information is determined at a dense distribution of points corresponding to points in the depth image. In one embodiment the depth information corresponding to the depth image is fed to actuators on sliding shafts in an array. Each sliding shaft is adjusted to the depth in the depth image to create a physical 3D topological surface like the surface or structure to be replicated.