58 citations · 191 across the 10 of their papers we have counts for
13 papers
Co-design Gym: A Unified Benchmark for Embodiment-Policy Co-optimization
Aviraj Newatia, Yordan Tsvetkov, Leonard Pleiss +2
Finding an optimal behaviour policy within a given environment is a widely studied problem in domains as diverse as games, robotics, energy infrastructure, communication networks,…
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma +6
Nature evolves creatures with a high complexity of morphological and behavioral intelligence, meanwhile computational methods lag in approaching that diversity and efficacy. Co-opt…
How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang +15
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the…
Efficient automatic design of robots
David Matthews, Andrew Spielberg, Daniela Rus +2
Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior. Despite this, almost ever…
Neural Fields with Hard Constraints of Arbitrary Differential Order
Fangcheng Zhong, Kyle Fogarty, Param Hanji +6
While deep learning techniques have become extremely popular for solving a broad range of optimization problems, methods to enforce hard constraints during optimization, particular…
SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments
Tsun-Hsuan Wang, Pingchuan Ma, Andrew Everett Spielberg +5
While significant research progress has been made in robot learning for control, unique challenges arise when simultaneously co-optimizing morphology. Existing work has typically b…
Zero-Shot Transfer of Haptics-Based Object Insertion Policies
Samarth Brahmbhatt, Ankur Deka, Andrew Spielberg +1
Humans naturally exploit haptic feedback during contact-rich tasks like loading a dishwasher or stocking a bookshelf. Current robotic systems focus on avoiding unexpected contact,…
Sim-to-Real for Soft Robots using Differentiable FEM: Recipes for Meshing, Damping, and Actuation
Mathieu Dubied, Mike Michelis, Andrew Spielberg +1
An accurate, physically-based, and differentiable model of soft robots can unlock downstream applications in optimal control. The Finite Element Method (FEM) is an expressive appro…
Multi-Objective Graph Heuristic Search for Terrestrial Robot Design
Jie Xu, Andrew Spielberg, Allan Zhao +2
We present methods for co-designing rigid robots over control and morphology (including discrete topology) over multiple objectives. Previous work has addressed problems in single-…
DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation
Pingchuan Ma, Tao Du, John Z. Zhang +4
The computational design of soft underwater swimmers is challenging because of the high degrees of freedom in soft-body modeling. In this paper, we present a differentiable pipelin…
DiffPD: Differentiable Projective Dynamics
Tao Du, Kui Wu, Pingchuan Ma +4
We present a novel, fast differentiable simulator for soft-body learning and control applications. Existing differentiable soft-body simulators can be classified into two categorie…
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
Yuanming Hu, Jiancheng Liu, Andrew Spielberg +5
Physical simulators have been widely used in robot planning and control. Among them, differentiable simulators are particularly favored, as they can be incorporated into gradient-b…
Functional Co-Optimization of Articulated Robots
Andrew Spielberg, Brandon Araki, Cynthia Sung +2
We present parametric trajectory optimization, a method for simultaneously computing physical parameters, actuation requirements, and robot motions for more efficient robot designs…