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Found 8 papers, 2 papers with code
How Can Large Language Models Help Humans in Design and Manufacturing?
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design.
AutoOED: Automated Optimal Experimental Design Platform with Data- and Time-Efficient Multi-Objective Optimization
We present AutoOED, an Automated Optimal Experimental Design platform powered by machine learning to accelerate discovering solutions with optimal objective trade-offs.
Closed-Loop Control of Additive Manufacturing via Reinforcement Learning
We further show that in combination with reinforcement learning, our model can be used to discover control policies that outperform state-of-the-art controllers.
Dynamic Modeling of Hand-Object Interactions via Tactile Sensing
This work takes a step on dynamics modeling in hand-object interactions from dense tactile sensing, which opens the door for future applications in activity learning, human-computer interactions, and imitation learning for robotics.
An End-to-End Differentiable Framework for Contact-Aware Robot Design
Existing methods for co-optimization are limited and fail to explore a rich space of designs.
Intelligent Carpet: Inferring 3D Human Pose From Tactile Signals
In this work, leveraging such tactile interactions, we propose a 3D human pose estimation approach using the pressure maps recorded by a tactile carpet as input.
Polygrammar: Grammar for Digital Polymer Representation and Generation
Here, we present a parametric, context-sensitive grammar designed specifically for the representation and generation of polymers.
AutoOED: Automated Optimal Experiment Design Platform
We present AutoOED, an Optimal Experiment Design platform powered with automated machine learning to accelerate the discovery of optimal solutions.
