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Automated Multi-Robot Assembly of Compliance Optimized StructuresAutonomous assembly of large structures is one of the fundamental challenges on the way towards NASA’s objectives of deep space exploration. In this work, we propose an algorithmic framework to optimize the assembly process of a prescribed target structure by constraining the assembly effort as well as maintaining structural soundness throughout the process. This framework uses structural topology optimization with assembly effort metrics to generate checkpoints for robotic traversal algorithms. Assembly effort is quantified by the Wasserstein metric between consecutive structural configurations during the assembly process. The robotic assembly task is split into two subtasks, where we first optimize for a set of key frames, then perform reconfiguration between consecutive frames. Key frames are optimized by adopting topology optimization techniques to reduce assembly effort and maintain structural integrity during the assembly process, while reconfiguration between key frames is performed using a path planning algorithm with a minimum weight maximum matching approach on a bipartite graph. We employ a Crystalline robot model in which each structural element is capable of locomotion through the structure and locking into place with neighboring elements after reaching its destination. An example assembly of a two-dimensional cantilever beam under volume constraints and structural compliance considerations is presented to demonstrate the approach. Finally, we conclude by discussing possible future extensions to this work, including adoption of better metrics, extension to three-dimensional large-scale problems, and exacting finer control of structural integrity during the path-planning phase.
Document ID
20240000491
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Yicong Fu
(Georgia Institute of Technology Atlanta, United States)
James Todd Gloyd
(Georgia Institute of Technology Atlanta, United States)
Irina Kostitsyna
(KBR (United States) Houston, Texas, United States)
Date Acquired
January 11, 2024
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: 45th International IEEE Aerospace Conference
Location: Big Sky, MT
Country: US
Start Date: March 2, 2024
End Date: March 9, 2024
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
CONTRACT_GRANT: 80ARC020D0010
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
topology optimization
automated assembly
robotic assembly
structural optimization
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