Semi-autonomous Digital Human Posturing with Collision Avoidance
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Solution Overview
Problem
Current digital human posturing methods in CAD and PDM systems are tedious and prone to non-optimal solutions, often requiring sophisticated hardware and manual intervention, and fail to account for real-life behaviors and environmental constraints.
Innovation Solution
A semi-autonomous system combining motion capture technologies with empirical posture prediction algorithms to rapidly and naturally posture digital human forms in virtual environments, allowing for intuitive control and collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used for digital human posturing, then control precision is improved, but operation time and complexity increase
Solution Approach 1:
The system enables semi-autonomous digital human posturing where the digital human automatically adjusts its posture based on motion capture data and environmental constraints. The posture prediction algorithm allows the system to self-adjust postures without continuous manual intervention, reducing operation time while maintaining precision through automated collision detection and posture optimization.
Solution Approach 2:
The patent replaces manual mechanical manipulation with automated computational methods. Motion capture data drives the posture prediction algorithm, which computationally determines optimal postures and detects collisions, substituting manual control with an automated system that processes motion data and generates postures efficiently.
2Measurement precision
If sophisticated hardware is used for motion capture, then motion data accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The system is designed to work with sparse motion capture data that can be obtained from simpler, more affordable sensors rather than requiring sophisticated motion capture hardware. The posture prediction algorithm compensates for the lower data quality, enabling the use of less expensive sensing equipment while still achieving accurate posturing results.
Solution Approach 2:
The patent changes the approach from requiring high-precision motion capture data to using sparse motion data with enhanced processing. By modifying the data processing parameters and using intelligent prediction algorithms, the system achieves accurate posturing with lower-quality input data, reducing hardware requirements.
3Device complexity
If traditional posturing methods are used, then system simplicity is maintained, but posturing accuracy and realism decrease
Solution Approach 1:
The patent introduces a posture prediction algorithm as an intermediary between motion capture data and digital human rendering. This intermediary layer processes sparse motion data, predicts realistic postures based on environmental constraints, and generates accurate digital human representations, bridging the gap between simple input data and high-accuracy output.
Solution Approach 2:
The system performs preliminary posture prediction and collision detection before finalizing the digital human posture. By pre-processing motion capture data and predicting optimal postures in advance, the system achieves higher accuracy without requiring complex real-time adjustments during the posturing process.
4Productivity
If environmental constraints are not considered, then posturing speed is improved, but posturing realism and accuracy decrease
Solution Approach 1:
The patent performs preliminary analysis of environmental constraints and object locations before generating postures. By pre-processing the environment data and identifying potential collision zones in advance, the system can quickly generate realistic postures that automatically respect environmental constraints, maintaining both speed and realism.
Solution Approach 2:
The system implements feedback through automated collision detection that monitors whether generated postures intersect with environmental objects. When collisions are detected, the posture prediction algorithm adjusts the posture to avoid intersections, providing real-time feedback that ensures realism while maintaining posturing speed through efficient collision checking.
Data Source
AI summary
Product Data Management systems, methods, and mediums. A method includes receiving data representing motion of a human generated by a motion capture device. The method includes identifying a generated posture of the human relative to objects in a virtual environment. The method includes determining whether the generated posture of the human intersects with an object in the virtual environment. Additionally, the method includes responsive to determining that the generated posture intersects with the object by a threshold amount, identifying a posture that will avoid intersection with the object by the threshold amount.