Adaptive, Intelligent Digital Twins to Enable In-Space Service, Assembly, and Manufacturing

Abstract

As space systems become vital to national defense, it is important to field more flexible capabilities more rapidly. In-space servicing, assembly, and manufacturing (ISAM) promises to accelerate development by deploying the tools to update or create new spacecraft free from launch design and schedule constraints. Fulfilling this promise will require capable autonomy to make ubiquitous, persistent systems that can operate with minimal support a reality. This poses a challenge in maintaining ongoing awareness of the state of artifacts being assembled as well as the ISAM system itself. Digital twins (DT) offer a solution to this challenge by continuously fusing sensed information about the configuration and state of these systems with digital models, forming a key enabler of space-based infrastructure development. However, there are many unresolved scientific and theoretical challenges associated with DT development, design, and deployment, especially in the space environment. To address these challenges, we propose to build a space-deployable digital engineering framework that can adaptively choose data and model quality, supporting robotic ISAM.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2025
Source ID
FA95502410176

Entities

People

  • Angel Flores-abad

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Texas at El Paso

Tags

Fields of Study

  • Computer science

Readers

  • Aerospace Engineering.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space