Automatic generation of object shapes with desired functionalities

TL;DR

This paper presents a novel AI-based method for automatically generating 3D object shapes that fulfill specified functionalities, significantly speeding up the traditional manual design process.

Contribution

It introduces an algorithm that learns a function-to-form mapping from labeled datasets and combines forms to generate objects with multiple desired functionalities.

Findings

Successfully generates object shapes with specified functionalities

Uses neural networks to learn form-function relationships

Verifies functionality through simulation tests

Abstract

3D objects (artefacts) are made to fulfill functions. Designing an object often starts with defining a list of functionalities that it should provide, also known as functional requirements. Today, the design of 3D object models is still a slow and largely artisanal activity, with few Computer-Aided Design (CAD) tools existing to aid the exploration of the design solution space. To accelerate the design process, we introduce an algorithm for generating object shapes with desired functionalities. Following the concept of form follows function, we assume that existing object shapes were rationally chosen to provide desired functionalities. First, we use an artificial neural network to learn a function-to-form mapping by analysing a dataset of objects labeled with their functionalities. Then, we combine forms providing one or more desired functions, generating an object shape that is expected to provide all of them. Finally, we verify in simulation whether the generated object possesses the desired functionalities, by defining and executing functionality tests on it.