Analysis and control of distributed cooperative systems.

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Description

As part of DARPA Information Processing Technology Office (IPTO) Software for Distributed Robotics (SDR) Program, Sandia National Laboratories has developed analysis and control software for coordinating tens to thousands of autonomous cooperative robotic agents (primarily unmanned ground vehicles) performing military operations such as reconnaissance, surveillance and target acquisition; countermine and explosive ordnance disposal; force protection and physical security; and logistics support. Due to the nature of these applications, the control techniques must be distributed, and they must not rely on high bandwidth communication between agents. At the same time, a single soldier must easily direct these large-scale systems. Finally, the ... continued below

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27 p.

Creation Information

Feddema, John Todd; Parker, Eric Paul; Wagner, John S. & Schoenwald, David Alan September 1, 2004.

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Description

As part of DARPA Information Processing Technology Office (IPTO) Software for Distributed Robotics (SDR) Program, Sandia National Laboratories has developed analysis and control software for coordinating tens to thousands of autonomous cooperative robotic agents (primarily unmanned ground vehicles) performing military operations such as reconnaissance, surveillance and target acquisition; countermine and explosive ordnance disposal; force protection and physical security; and logistics support. Due to the nature of these applications, the control techniques must be distributed, and they must not rely on high bandwidth communication between agents. At the same time, a single soldier must easily direct these large-scale systems. Finally, the control techniques must be provably convergent so as not to cause undo harm to civilians. In this project, provably convergent, moderate communication bandwidth, distributed control algorithms have been developed that can be regulated by a single soldier. We have simulated in great detail the control of low numbers of vehicles (up to 20) navigating throughout a building, and we have simulated in lesser detail the control of larger numbers of vehicles (up to 1000) trying to locate several targets in a large outdoor facility. Finally, we have experimentally validated the resulting control algorithms on smaller numbers of autonomous vehicles.

Physical Description

27 p.

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  • Report No.: SAND2004-4763
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/919643 | External Link
  • Office of Scientific & Technical Information Report Number: 919643
  • Archival Resource Key: ark:/67531/metadc901058

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Creation Date

  • September 1, 2004

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

Description Last Updated

  • Dec. 6, 2016, 6:59 p.m.

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Feddema, John Todd; Parker, Eric Paul; Wagner, John S. & Schoenwald, David Alan. Analysis and control of distributed cooperative systems., report, September 1, 2004; United States. (digital.library.unt.edu/ark:/67531/metadc901058/: accessed September 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.