papers

Publications (23)

cs.RO2024

Reinforcement learning for freeform robot design

Muhan Li, David Matthews, Sam Kriegman

Inspired by the necessity of morphological adaptation in animals, a growing body of work has attempted to expand robot training to encompass physical aspects of a robot's design. H…

cs.RO2026

Robots that redesign themselves through kinematic self-destruction

Chen Yu, Sam Kriegman

Every robot built to date was predesigned by an external process, prior to deployment. Here we show a robot that actively participates in its own design during its lifetime. Starti…

cs.RO2019

Automated shapeshifting for function recovery in damaged robots

Sam Kriegman, Stephanie Walker, Dylan Shah +3

A robot's mechanical parts routinely wear out from normal functioning and can be lost to injury. For autonomous robots operating in isolated or hostile environments, repair from a…

cs.RO2021

Scale invariant robot behavior with fractals

Sam Kriegman, Amir Mohammadi Nasab, Douglas Blackiston +4

Robots deployed at orders of magnitude different size scales, and that retain the same desired behavior at any of those scales, would greatly expand the environments in which the r…

cs.RO2024

Generating Freeform Endoskeletal Robots

Muhan Li, Lingji Kong, Sam Kriegman

The automatic design of embodied agents (e.g. robots) has existed for 31 years and is experiencing a renaissance of interest in the literature. To date however, the field has remai…

cs.RO2026

Creating manufacturable blueprints for coarse-grained virtual robots

Zihan Guo, Muhan Li, Shuzhe Zhang +1

Over the past three decades, countless embodied yet virtual agents have freely evolved inside computer simulations, but vanishingly few were realized as physical robots. This is be…

cs.AI2018

Interoceptive robustness through environment-mediated morphological development

Sam Kriegman, Nick Cheney, Francesco Corucci +1

Typically, AI researchers and roboticists try to realize intelligent behavior in machines by tuning parameters of a predefined structure (body plan and/or neural network architectu…

cs.NE2017

A Minimal Developmental Model Can Increase Evolvability in Soft Robots

Sam Kriegman, Nick Cheney, Francesco Corucci +1

Different subsystems of organisms adapt over many time scales, such as rapid changes in the nervous system (learning), slower morphological and neurological change over the lifetim…

stat.ML2017

Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling

Sam Kriegman, Marcin Szubert, Josh C. Bongard +1

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for…

cs.RO2019

Scalable sim-to-real transfer of soft robot designs

Sam Kriegman, Amir Mohammadi Nasab, Dylan Shah +5

The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools. Mac…

cs.RO2026

Computational Design of a Low-Visibility UAV Using a Human-Aligned Perceptual Metric

Jingxian Wang, Chen Yu, David Matthews +3

We introduce Phantom Twist, a type of single-propeller UAV designed to achieve low visibility through high-speed spinning and the exploitation of motion blur. We develop a two-stag…

cs.RO2025

Accelerated co-design of robots through morphological pretraining

Luke Strgar, Sam Kriegman

The co-design of robot morphology and neural control typically requires using reinforcement learning to approximate a unique control policy gradient for each body plan, demanding m…

cs.CL2019

Word2vec to behavior: morphology facilitates the grounding of language in machines

David Matthews, Sam Kriegman, Collin Cappelle +1

Enabling machines to respond appropriately to natural language commands could greatly expand the number of people to whom they could be of service. Recently, advances in neural net…

cs.AI2018

Combating catastrophic forgetting with developmental compression

Shawn L. E. Beaulieu, Sam Kriegman, Josh C. Bongard

Generally intelligent agents exhibit successful behavior across problems in several settings. Endemic in approaches to realize such intelligence in machines is catastrophic forgett…

cs.RO2024

Evolution and learning in differentiable robots

Luke Strgar, David Matthews, Tyler Hummer +1

The automatic design of robots has existed for 30 years but has been constricted by serial non-differentiable design evaluations, premature convergence to simple bodies or clumsy b…

cs.RO2026

ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots

Yibin Wang, Muhan Li, Zihan Guo +1

In this paper, we introduce a model of evolution and learning in robots that co-optimizes a distribution of latent design vectors (genotypes) and a mixture of control experts (neur…

cs.RO2023

A soft robot that adapts to environments through shape change

Dylan S. Shah, Joshua P. Powers, Liana G. Tilton +3

Many organisms, including various species of spiders and caterpillars, change their shape to switch gaits and adapt to different environments. Recent technological advances, rangin…

cs.RO2026

Agile legged locomotion in reconfigurable modular robots

Chen Yu, David Matthews, Jingxian Wang +4

Legged machines are becoming increasingly agile and adaptive but they have so far lacked the morphological diversity of legged animals, which have been rearranged and reshaped to f…

cs.RO2024

A non-cubic space-filling modular robot

Tyler Hummer, Sam Kriegman

Space-filling building blocks of diverse shape permeate nature at all levels of organization, from atoms to honeycombs, and have proven useful in artificial systems, from molecular…

cs.RO2023

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…

cs.LG2021

Embodiment dictates learnability in neural controllers

Joshua Powers, Ryan Grindle, Sam Kriegman +3

Catastrophic forgetting continues to severely restrict the learnability of controllers suitable for multiple task environments. Efforts to combat catastrophic forgetting reported i…

q-bio.PE2018

How morphological development can guide evolution

Sam Kriegman, Nick Cheney, Josh Bongard

Organisms result from adaptive processes interacting across different time scales. One such interaction is that between development and evolution. Models have shown that developmen…

cs.AI2023

Glamour muscles: why having a body is not what it means to be embodied

Shawn L. Beaulieu, Sam Kriegman

Embodiment has recently enjoyed renewed consideration as a means to amplify the faculties of smart machines. Proponents of embodiment seem to imply that optimizing for movement in…