3D GUI for Complex Object Manipulation

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Solution Overview

Problem

Conventional 2D graphical user interfaces (GUIs) face challenges in providing comprehensive and intuitive interactions with 3D objects, particularly in terms of angular displacement and depth value representation, which limits their ability to control complex 3D devices like robots with multiple degrees of freedom, and requires significant CPU/GPU resources for matrix transformation.

Innovation Solution

A 3D graphical user interface (GUI) that utilizes high-resolution, high-sensitivity 3D navigational devices to provide absolute addresses and linear and non-linear motion vectors, enabling direct manipulation of 3D objects with six degrees of freedom, and incorporates artificial intelligence features like machine learning to enhance user engagement and efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional 2D GUI is used to interact with 3D objects, then the interface is simple to implement, but the ability to control complex 3D devices with multiple degrees of freedom is limited

Engineering Contradiction:
Improveability to control complex 3D devicesVSAvoidinterface complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent transitions from conventional 2D GUI to a 3D GUI that operates in three-dimensional space, allowing users to interact with 3D objects directly. The system provides six-degree-of-freedom control (three translational and three rotational) enabling comprehensive manipulation of complex 3D devices while maintaining intuitive interaction through spatial metaphors rather than complex parameter adjustments.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Productivity

If conventional 2D GUI with matrix transformation is used, then the implementation is straightforward, but significant CPU/GPU resources are required

Engineering Contradiction:
Improveinteraction efficiencyVSAvoidCPU/GPU resource consumption
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The patent replaces traditional matrix transformation methods with a 3D coordinate system approach that uses direction cosines and spatial vectors. This substitution eliminates the need for computationally intensive matrix operations while achieving the same 3D positioning and orientation results, thereby reducing CPU/GPU resource consumption and improving interaction efficiency.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Loss of information

If conventional 2D GUI is used, then the display is simple, but angular displacement and depth value representation are limited

Engineering Contradiction:
Improveangular displacement and depth informationVSAvoiddisplay complexity
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent implements a 3D display system that preserves and visualizes angular displacement and depth value information through three-dimensional graphical representations. The system renders 3D objects with proper perspective, occlusion, and spatial relationships, allowing users to perceive depth and orientation directly rather than through limited 2D projections, thus preventing information loss while maintaining display clarity through natural 3D visualization.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS11307730B2Pervasive 3D graphical user interface configured for machine learning
Publication Date: 2022.04.19 WEN CHIEH GEOFFREY LEE
  • US11307730B2 patent drawing
  • US11307730B2 patent drawing
  • US11307730B2 patent drawing

AI summary

A three-dimensional graphical user interface (3D GUI) configured to be used by a computer, a display system, an electronic system, or an electro-mechanical system. The 3D GUI provides an enhanced user-engaging experience while enabling a user to manipulate the motion of an object of arbitrary size and a multiplicity of independent degrees of freedom, using sufficient degrees of freedom to represent the motion. The 3D GUI includes the functionality of machine learning (ML), which uses support vector machine (SVM) and/or convolutional neural network (CNN) to provide intelligent control of robot kinematics and computer graphics as well as the ability of the user to more quickly learn the more subtle applications of 3D computer graphics.