A multiagent methodology for lunar robotic mission risk mitigation

E. J P Earon, J. Thangavelautham, T. Liu, H. Armstrong, G. M T D'Eleuterio, D. Boucher, M. Viel, J. Richard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The proposed return to the Moon by 2020 will represent one of the one of the most dramatic and challenging steps in human exploration as the international community prepares to establish a permanent presence, a homestead in the ultimate frontier. Prior to sending humans, however, there will be a number of robotic precursor missions. Even after humans alight on our closest celestial neighbor, robots will continue to play a crucial role, performing tasks that are too dangerous or even too mundane for astronauts. We must accordingly seek to mitigate mission risk whenever and wherever possible. Excavation tasks, for building landing pads, constructing habitats and generally establishing infrastructure, will undoubtedly be delegated to robotic systems. We propose that a multiagent methodology will be required to successfully accomplish these tasks and mitigate the associated risks. However, a multiagent approach in an unstructured environment will pose significant control challenges. We present a control architecture and philosophy for multiagent robotic systems. Such a system has been implemented in computer simulation and in a representative network of small laboratory rovers. The control paradigm is based on a flexible machine learning algorithm, which we call an "artificial neural tissue." An evolutionary approach, that is, an artificial Darwinian selection process, is used to derive the control strategy in computer simulation. The result of this process can then be directly ported to the physical system to accomplish the desired tasks.

Original languageEnglish (US)
Title of host publicationAIAA Space 2009 Conference and Exposition
StatePublished - 2009
Externally publishedYes
EventAIAA Space 2009 Conference and Exposition - Pasadena, CA, United States
Duration: Sep 14 2009Sep 17 2009

Other

OtherAIAA Space 2009 Conference and Exposition
CountryUnited States
CityPasadena, CA
Period9/14/099/17/09

Fingerprint

Robotics
Computer simulation
Moon
Landing
Excavation
Learning algorithms
Learning systems
Robots
Tissue

ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Earon, E. J. P., Thangavelautham, J., Liu, T., Armstrong, H., D'Eleuterio, G. M. T., Boucher, D., ... Richard, J. (2009). A multiagent methodology for lunar robotic mission risk mitigation. In AIAA Space 2009 Conference and Exposition [2009-6794]

A multiagent methodology for lunar robotic mission risk mitigation. / Earon, E. J P; Thangavelautham, J.; Liu, T.; Armstrong, H.; D'Eleuterio, G. M T; Boucher, D.; Viel, M.; Richard, J.

AIAA Space 2009 Conference and Exposition. 2009. 2009-6794.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Earon, EJP, Thangavelautham, J, Liu, T, Armstrong, H, D'Eleuterio, GMT, Boucher, D, Viel, M & Richard, J 2009, A multiagent methodology for lunar robotic mission risk mitigation. in AIAA Space 2009 Conference and Exposition., 2009-6794, AIAA Space 2009 Conference and Exposition, Pasadena, CA, United States, 9/14/09.
Earon EJP, Thangavelautham J, Liu T, Armstrong H, D'Eleuterio GMT, Boucher D et al. A multiagent methodology for lunar robotic mission risk mitigation. In AIAA Space 2009 Conference and Exposition. 2009. 2009-6794
Earon, E. J P ; Thangavelautham, J. ; Liu, T. ; Armstrong, H. ; D'Eleuterio, G. M T ; Boucher, D. ; Viel, M. ; Richard, J. / A multiagent methodology for lunar robotic mission risk mitigation. AIAA Space 2009 Conference and Exposition. 2009.
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