Simulate and design “xenobots”, on the AMD platform

Project Title: Simulate and design “xenobots”, on the AMD platform
Program:
Northeast (308)

Project Image: https://support.access-ci.org/system/files/webform/project/211/xenobot.jpeg
Tags:
administering-hpc (438), amber (292), big-data (4), biology (515), file-transfer (252), github (490), slurm (71)

Status: Complete
Project Leader
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Project Leader:
Josh  Bongard

Email: aelledge@uvm.edu
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Project Personnel
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Mentor(s):
Keri Toksu (508)

Student-facilitator(s):
David Matthews (179)

Mentee(s):
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Project Information
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Project Description:
In a previous project, undergraduate David Matthews ported our voxel-based soft-bodied physical simulator, Voxcraft, to the AMD platform. This allows us to simulate and design “xenobots” -- mm-sized robots made exclusively from genetically unmodified frog tissue —on the AMD platform.

In the new project we propose, Matthews will draw on his experience with AMD from the previous platform to port a next-generation soft-body simulator to the AMD platform. This new simulator is based on the material-point method (MPM), which is rapidly becoming the standard approach for simulating machines and robots with soft and/or biological components. This is because MPM allows state-of-art AI methods to design soft-bodied machines much more efficiently. More specifically, it allows for the backpropagation of behavioral error — where the machine “went wrong” in trying to perform the desired task — into the design and control of the machine itself. This allows the AI to avoid computationally inefficient trial and error design, and instead assume gradient-based design. We propose three deliverables for this project.

Project Information Subsection
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Project Deliverables:
1. In the first month, we will port the Material Point Method to the AMD cluster. This will result in the creation of a series of videos showing hand-built robots, in silico, as a connected series of points, behaving in a virtual world.

2. In the second month we will wrap a gradient-based AI method around this MPM simulator, and demonstrate how it can propagate behavioral errors back through the simulator to fix errors in the shape and control of the robot.

3. In the final month we will show how the AI method can efficiently design these robots to perform a series of simple tasks, and demonstrate that some of these AI-designed robots could actually be fabricated, in reality, as xenobots built from frog tissues.

Project Deliverables:
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Student Research Computing Facilitator Profile:
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Mentee Research Computing Profile:
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Student Facilitator Programming Skill Level: Can work with any level
Mentee Programming Skill Level: {Empty}
Project Institution: University of Vermont
Project Address:
89 S. Prospect Street
Burlington, Vermont. 05405

Anchor Institution: NE-University of Vermont
Preferred Start Date: 10/01/2021
Start as soon as possible.: No
Project Urgency: Already behind3Start date is flexible
Expected Project Duration (in months): 3
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Launch Presentation Date: {Empty}
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Project Milestones:
- Milestone Title: Videos of hand built robots
  Milestone Description: Port the Material Point Method to the AMD cluster. This will result in the creation of a series of videos showing hand-built robots, in silico, as a connected series of points, behaving in a virtual world.
  Completion Date Goal: 2021-10-31

Github Contributions: {Empty}
Planned Portal Contributions (if any):
Will add questions to the portal

Planned Publications (if any):
yes at least on paper

What will the student learn?:
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What will the mentee learn?:
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What will the Cyberteam program learn from this project?:
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HPC resources needed to complete this project?:
VACC cluster access to both DeepGreen and AMD gpu clusters

Notes:
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Final Report
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What is the impact on the development of the principal discipline(s) of the project?:
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What is the impact on other disciplines?:
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Is there an impact physical resources that form infrastructure?:
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Is there an impact on the development of human resources for research computing?:
From student David Matthews, BS Computer Science UVM 2021
Since the NE Cyberteam grant I have been continuing to work with professor Josh Bongard on developing a new method to efficiently optimize the topology of soft robots. We are getting close to publishing this work.
In addition I am planning to apply to Ph.D programs in AI and robotics this fall.

Is there an impact on institutional resources that form infrastructure?:
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Is there an impact on information resources that form infrastructure?:
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Is there an impact on technology transfer?:
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Is there an impact on society beyond science and technology?:
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Lessons Learned:
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Overall results:
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