Fast Movements, Impacts and Deformations: Nature, Robotics and Materials

Abstract

This symposium will bring our MURI team research effort on Latch Mediated Spring Actuation (LaMSA) systems to the broader scientific and engineering communities. The world of extremely small, high acceleration systems that can be used repeatedly and repeatably remains iconic in biology and largely out of reach in synthetic systems. Through the MURI team effort, we have established a broad conceptual, mathematical, and experimental framework (LaMSA) that is enabling a community-wide, multidisciplinary effort to measure, characterize and synthesize these systems in a coherent and forward-looking way. However, many enabling elements of LaMSA systems are also critical to other important challenges for engineering and science fields. In organizing this symposium, our goal is to establish a forum that unites researchers who focus on such elements and includes researchers who have yet to directly inform their research through principles of LaMSA systems. We aim to not only advance understanding of both biological and synthetic LaMSA systems but also to build connections that will have a positive, significant impact across a wide range of related challenges. The symposium will be held in July 2022 at Duke University, Durham, NC, at a site that allows for all attendees to share informal and formal sessions that focus on scientific exchange and advancement. This proposal requests funding to support the lodging and partial travel expenses for the invited session chairs, session speakers, organizers, and early career stage participants.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 14, 2022
Source ID
W911NF2210101

Entities

People

  • Sheila Patek

Organizations

  • Army Contracting Command
  • Duke University
  • United States Army

Tags

Readers

  • Academic Conference Management
  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Autonomy