Award Abstract # 1830870
EFRI C3 SoRo: Programmable Skins for Moldable and Morphogenetic Soft Robots

NSF Org: EFMA
Office of Emerging Frontiers in Research and Innovation (EFRI)
Recipient: YALE UNIV
Initial Amendment Date: August 16, 2018
Latest Amendment Date: February 2, 2022
Award Number: 1830870
Award Instrument: Standard Grant
Program Manager: Jordan Berg
jberg@nsf.gov
 (703)292-5365
EFMA
 Office of Emerging Frontiers in Research and Innovation (EFRI)
ENG
 Directorate for Engineering
Start Date: October 1, 2018
End Date: September 30, 2023 (Estimated)
Total Intended Award Amount: $2,000,000.00
Total Awarded Amount to Date: $2,120,522.00
Funds Obligated to Date: FY 2018 = $2,000,000.00
FY 2019 = $16,000.00

FY 2020 = $23,800.00

FY 2021 = $16,000.00

FY 2022 = $64,722.00
History of Investigator:
  • Rebecca Kramer-Bottiglio (Principal Investigator)
    rebecca.kramer@yale.edu
  • Joshua Bongard (Co-Principal Investigator)
  • Michael Levin (Co-Principal Investigator)
  • Madhusudhan Venkadesan (Co-Principal Investigator)
Recipient Sponsored Research Office: Yale University
150 MUNSON ST
NEW HAVEN
CT  US  06511-3572
(203)785-4689
Sponsor Congressional District: 03
Primary Place of Performance: Yale University
9 Hillhouse Avenue
New Haven
CT  US  06520-8286
Primary Place of Performance
Congressional District:
03
Unique Entity Identifier (UEI): FL6GV84CKN57
Parent UEI: FL6GV84CKN57
NSF Program(s): EFRI Research Projects
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT

01001819RB NSF RESEARCH & RELATED ACTIVIT

01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7633, 9102, 9231, 9251
Program Element Code(s): 763300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

This project seeks to address the problem of preparing a robot to perform a set of known tasks, despite the lack of any information about the task to be performed or the environment in which it occurs. The approach taken is to construct an active robotic skin, integrating motion, sensing, and decision-making into a single conformable material skin with embedded sensors and actuators, and wrap it around a passive, moldable core material. The skin acts to deform the core, in such a way as to make the robot move, in a manner which is optimized for its surroundings using evolutionary algorithms. In preliminary work, the PI team has demonstrated an initially spherical robot first causing itself to roll, and then morphing to a cylinder and switching to an inchworm-type gait. This project will leverage novel insights from biological systems to derive new operational principles for robots capable of editing their own algorithmic control structure to make use of a changing anatomy, enabling more robust functionality. The results of this research will enable morphing robots that can adjust their morphology to accomplish different tasks or move more efficiently to meet the demands of changing environments or contexts. This project addresses the producing of a transformative tool that can adapt for exploration or discovery of unknown, dangerous, or unpredictable environments.

Rigid-bodied robots generally excel at specific tasks in structured environments, but lack the versatility and adaptability required to interact-with and locomote-within the natural world. This project will introduce robotic skins that wrap around arbitrary soft bodies to induce the desired motions and deformations. With the addition of robotic skins, passive soft bodies may be turned into active soft robots. Robotic skins integrate actuation, sensing, variable stiffness, and computation into a single conformable material, and may be leveraged to create morphing robots capable of editing their own morphology and control in unstructured and dynamic environments. The objective of the proposed work is to develop and implement an end-to-end procedure that begins with behavior specifications and ends with a physical self-morphing soft robot and its software environment. The approach will employ robotic skins as the foundation of morphing machines by wrapping them around moldable materials (e.g. clay), enabling surface-driven shape change. Robotic skins will mold the underlying body into a desired shape through controlled surface strains, surface pressures and selective stiffening. As the environment or task changes, the skin will re-mold the body into a new shape that is optimized for its context. This approach will leverage novel insights from diverse biological systems to derive new mathematical models, evolutionary algorithms, and multifunctional materials to enable unparalleled contextually-sensitive morphing capabilities for soft robots.

This project is jointly sponsored by the National Science Foundation, Office of Emerging Frontiers and Multidisciplinary Activities (EFMA) and the US Air Force Office of Scientific Research (AFOSR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 25)
Bilodeau, R. Adam and Mohammadi Nasab, Amir and Shah, Dylan S. and Kramer-Bottiglio, Rebecca "Uniform conductivity in stretchable silicones via multiphase inclusions" Soft Matter , v.16 , 2020 10.1039/D0SM00383B Citation Details
Blackiston, Douglas and Kriegman, Sam and Bongard, Josh and Levin, Michael "Biological Robots: Perspectives on an Emerging Interdisciplinary Field" Soft Robotics , v.10 , 2023 https://doi.org/10.1089/soro.2022.0142 Citation Details
Buckner, Trevor L. and Yuen, Michelle C. and Kim, Sang Yup and KramerBottiglio, Rebecca "Enhanced Variable Stiffness and Variable Stretchability Enabled by PhaseChanging Particulate Additives" Advanced Functional Materials , 2019 10.1002/adfm.201903368 Citation Details
Davis, Q. Tyrell and Bongard, Josh "Glaberish: Generalizing the Continuously-Valued Lenia Framework to Arbitrary Life-Like Cellular Automata" Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life , 2022 https://doi.org/10.1162/isal_a_00530 Citation Details
Davis, Q. Tyrell and Bongard, Josh "Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesis" Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '22) , 2022 https://doi.org/10.1145/3520304.3529037 Citation Details
Davis, Q. Tyrell and Bongard, Josh "Step Size is a Consequential Parameter in Continuous Cellular Automata" Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life , 2022 https://doi.org/10.1162/isal_a_00526 Citation Details
Davis, Q. Tyrell and Woodman, Stephanie and Landesberg, Melanie and Kramer-Bottiglio, Rebecca and Bongard, Josh "Subtract to Adapt: Autotomic Robots" , 2023 https://doi.org/10.1109/RoboSoft55895.2023.10122102 Citation Details
Eristoff, Sophia and Kim, Sang Yup and SanchezBotero, Lina and Buckner, Trevor and Yirmibeolu, Osman Doan and KramerBottiglio, Rebecca "Soft Actuators Made of Discrete Grains" Advanced Materials , v.34 , 2022 https://doi.org/10.1002/adma.202109617 Citation Details
Kriegman, Sam and Mohammadi Nasab, Amir and Blackiston, Douglas and Steele, Hannah and Levin, Michael and Kramer-Bottiglio, Rebecca and Bongard, Josh "Scale invariant robot behavior with fractals" Proceedings of Robotics: Science and Systems , 2021 https://doi.org/10.15607/RSS.2021.XVII.059 Citation Details
Kriegman, Sam and Nasab, Amir Mohammadi and Shah, Dylan and Steele, Hannah and Branin, Gabrielle and Levin, Michael and Bongard, Josh and Kramer-Bottiglio, Rebecca "Scalable sim-to-real transfer of soft robot designs" 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft) , 2020 10.1109/RoboSoft48309.2020.9116004 Citation Details
Kriegman, Sam and Walker, Stephanie and Shah, Dylan and Levin, Michael and Kramer-Bottiglio, Rebecca and Bongard, Josh "Automated shapeshifting for function recovery in damaged robots" Proceedings of Robotics: Science and Systems (2019) , 2019 10.15607/RSS.2019 Citation Details
(Showing: 1 - 10 of 25)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Soft robots offer a unique potential to adapt to various tasks and environments by adjusting their morphology, properties, and behavioral control. This project aimed to develop and utilize robotic skins as the basis for morphing robots, wrapping them around moldable materials such as clay to enable surface-driven shape change. These skins, equipped with embedded actuation, sensing, and variable stiffness components, would apply surface strains and pressures to a moldable body, influencing both its shape and behavior. The goal was to design robotic skins that could facilitate morphing between at least two shapes and the behaviors associated with them.
During the project, our focus shifted to exploring methods and benefits of shape change more broadly. While achieving robots with adaptive morphology using robotic skins proved challenging, we introduced multiple platforms for shape-changing robots. These platforms were then used to investigate the energetics of morphing (assessing if the energy cost of morphing outweighed the task efficiency gained in an optimal shape) and real-time optimization based on limited environmental perception (determining how and when a robot should change shape during transitions between environments).
Key outcomes of this project include 1) A definition of shape-changing robots focusing on functional adaptation rather than strict shape metrics; 2) Advances in robotic skin hardware, including new materials, components, and approaches to skin-based sensing and variable stiffness; 3) Development of a simulation-to-reality pipeline enabling direct translation of robots simulated in Voxcraft to real robots made from soft inflatable "voxels," which facilitated the study of automated shapeshifting for damage recovery and shape change through material loss (autotomy); and 4) Creation of a reality-to-simulation-to-reality pipeline using tensile jamming fibers patterned on inflatable sheets, which was used to study the effectiveness of evolutionary algorithms in optimizing fiber patterns for shape matching and using shape-similarity criteria to combine multiple fiber patterns.
Additionally, this project placed a strong emphasis on education and outreach. We developed and piloted an interactive soft robotics collaborative gaming platform, Twitch Plays Soft Robotics (TPSR), where users can collaboratively control a real soft robot via live streaming. We believe that interacting with TPSR can help users learn about the challenges associated with soft robot control.

Last Modified: 03/14/2024
Modified by: Rebecca Kramer-Bottiglio

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