Co-generating Collision-Free Shapes for Interacting Objects
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Solution Overview
Problem
Existing methods for generating shapes of mechanical assemblies with complex relative motions face challenges in avoiding collisions and interference, as they often require arbitrary geometric choices and do not allow for simultaneous optimization of multiple interacting components, leading to suboptimal designs.
Innovation Solution
A system and method for automatically generating collision-free shapes of multiple interacting objects based on arbitrary motions, using topology optimizations and sensitivity fields augmented by gradients and local collision measures, which enables simultaneous generation of geometric representations that avoid interference and maintain contact, allowing for additive manufacturing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If arbitrary geometric choices are made for one part's shape to compute maximal shape of another part using unsweep operation, then collision-free shape generation is achieved, but design space restrictions increase and multiple interactive components cannot be simultaneously optimized
Solution Approach 1:
The patent merges the shape generation processes of multiple interactive components into a single simultaneous optimization framework. Instead of sequentially generating shapes for individual parts with arbitrary geometric choices, the system formulates a unified optimization problem that considers all interacting components (e.g., cam and follower) together, allowing their shapes to be co-optimized while maintaining collision-free constraints throughout their relative motions.
Solution Approach 2:
The patent introduces dynamics by making the geometric parameters of multiple components variable and interdependent during the optimization process. The shape parameters of interacting parts are treated as dynamic design variables that can adjust simultaneously to achieve optimal collision-free configurations, rather than fixing one part's geometry arbitrarily before designing the other.
2Device complexity
If sequential shape generation is used where one part's shape is fixed first, then computational simplicity is maintained, but optimization of multiple interactive components is prevented
Solution Approach 1:
The patent applies preliminary action by pre-defining the relative motion constraints and interaction conditions between components before initiating the simultaneous optimization process. The kinematic relationships, motion paths, and collision constraints are established in advance as fixed parameters, while the shape geometries of all interacting components are then optimized together based on these pre-set conditions, achieving both computational tractability and design optimality.
3Reliability
If maximal collision-free pointsets are computed using configuration space modeling techniques, then collision avoidance is ensured, but arbitrary geometric choices place unnecessary restrictions on design space
Solution Approach 1:
The patent employs parameter changes by transforming the collision avoidance problem from a geometric constraint satisfaction problem into a parametric optimization problem. Instead of computing maximal collision-free pointsets with fixed arbitrary geometries, the system defines shape parameters of multiple components as variable parameters and uses optimization algorithms to find parameter values that simultaneously satisfy collision-free constraints and maximize design flexibility, enabling continuous exploration of the design space.
Data Source
AI summary
The present disclosure provides techniques for automatically generating shapes (e.g., geometric representations) of two or more interacting objects based on arbitrary motions specified for the two or more interacting objects. In an example system. the system receives specifications of motions or movements of two or more objects and the associated design spaces and generates collision-free shapes for the two or more objects while the two or more objects undergo the specified motions. As such, the system solves for unknown or undefined shapes based on desired motion profiles. For example, given respective movement or motion characterizations of two or more objects, such as at least one of a function translation or a function rotation over time in at least one of the three axes in a Euclidean space, topology optimizations may be performed to generate the respective shapes or geometric representations of the two or more objects.