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Robotic Specialization in Autonomous Robotic Structural AssemblyRobotic in-space assembly of large space structures is a long-term NASA goal to reduce launch costs and enable larger scale missions. Recently, researchers have proposed using discrete lattice building blocks and co-designed robots to build high-performance, scalable primary structure for various on-orbit and surface applications. These robots would locomote on the lattice and work in teams to build and reconfigure building-blocks into functional structure. However, the most reliable and efficient robotic system architecture, characterized by the number of different robotic 'species' and the allocation of functionality between species, is an open question. To address this problem, we decompose the robotic building-block assembly task into functional primitives and, in simulation, study the performance of the the variety of possible resulting architectures. For a set consisting of five process types (move self, move block, move friend, align bock, fasten block), we describe a method of feature space exploration and ranking based on energy and reliability cost functions. The solution space is enumerated, filtered for unique solutions, and evaluated against energy and reliability cost functions for various simulated build sizes. We find that a 2 species system, dividing the five mentioned process types between one unit cell transport robot and one fastening robot, results in the lowest energy cost system, at some cost to reliability. This system enables fastening functionality to occupy the build front while reducing the need for that functional mass to travel back and forth from a feed station. Because the details of a robot design affect the weighting and final allocation of functionality, a sensitivity analysis was conducted to evaluate the effect of changing mass allocations on architecture performance. Future systems with additional functionalities such as repair, inspection, and others may use this process to analyze and determine alternative robot architectures.
Document ID
20200001509
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Bernus, Borbala
(Välkommen Till Kth Stockholm, Sweden)
Trinh, Greenfield
(Stinger Ghaffarian Technologies Inc. (SGT Inc.) Moffett Field, CA, United States)
Gregg, Christine
(NASA Ames Research Center Moffett Field, CA, United States)
Formoso, Olivia
(Stinger Ghaffarian Technologies Inc. (SGT Inc.) Moffett Field, CA, United States)
Cheung, Kenneth
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
March 11, 2020
Publication Date
March 7, 2020
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Report/Patent Number
ARC-E-DAA-TN77099
Meeting Information
Meeting: IEEE Aerospace Conference
Location: Big Sky, MT
Country: United States
Start Date: March 7, 2020
End Date: March 14, 2020
Sponsors: Institute of Electrical and Electronics Engineers (IEEE)
Funding Number(s)
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
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