DiffuseBot Uses Generative AI To Invent New Soft Robots
DiffuseBot uses physics-augmented generative diffusion models to create robotic solutions to real-world problems.
Nature evolves creatures with a high complexity of morphological and behavioral
intelligence, meanwhile computational methods lag in approaching that diversity
and efficacy. Co-optimization of artificial creatures’ morphology and control in
silico shows promise for applications in physical soft robotics and virtual character
creation; such approaches, however, require developing new learning algorithms
that can reason about function atop pure structure.
In this paper, we present DiffuseBot, a physics-augmented diffusion model that generates soft robot morphologies
capable of excelling in a wide spectrum of tasks. DiffuseBot bridges the gap
between virtually generated content and physical utility by (i) augmenting the
diffusion process with a physical dynamical simulation which provides a certificate
of performance, and ii) introducing a co-design procedure that jointly optimizes
physical design and control by leveraging information about physical sensitivities
from differentiable simulation.
The robot mother from The Mechanical Mice, by Maurice G. Hugi, published by Astounding Stories in 1941, was described as an autonomous and creative robot that designed and made a series of helper robots, that could go out and get materials and parts - to make more robots.
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