Simulate and design “xenobots”, on the AMD platform

Project Information

administering-hpc, amber, big-data, biology, file-transfer, github, slurm
Project Status: Complete
Project Region: Northeast
Submitted By: Andrea Elledge
Project Email: aelledge@uvm.edu
Project Institution: University of Vermont
Anchor Institution: NE-University of Vermont
Project Address: 89 S. Prospect Street
Burlington, Vermont. 05405

Mentors: Keri Toksu
Students: David Matthews

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

administering-hpc, amber, big-data, biology, file-transfer, github, slurm
Project Status: Complete
Project Region: Northeast
Submitted By: Andrea Elledge
Project Email: aelledge@uvm.edu
Project Institution: University of Vermont
Anchor Institution: NE-University of Vermont
Project Address: 89 S. Prospect Street
Burlington, Vermont. 05405

Mentors: Keri Toksu
Students: David Matthews

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.