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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:NEVADA SYSTEM OF HIGHER EDUCATION
Doing Business As Name:Board of Regents, NSHE, obo University of Nevada, Reno
PD/PI:
  • George Bebis
  • (775) 784-6463
  • bebis@cse.unr.edu
Award Date:09/09/2009
Estimated Total Award Amount: $ 599,970
Funds Obligated to Date: $ 599,970
  • FY 2009=$599,970
Start Date:09/01/2009
End Date:08/31/2013
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040101 RRA RECOVERY ACT
Award Title or Description:CPS: Small: Real-time, Simulation-based Planning and Asynchronous Coordination for Cyber-Physical Systems
Federal Award ID Number:0932423
DUNS ID:146515460
Parent DUNS ID:067808063
Program:CYBER-PHYSICAL SYSTEMS (CPS)
Program Officer:
  • David Corman
  • (703) 292-8754
  • dcorman@nsf.gov

Awardee Location

Street:1664 North Virginia Street
City:Reno
State:NV
ZIP:89557-0001
County:Reno
Country:US
Awardee Cong. District:02

Primary Place of Performance

Organization Name:Board of Regents, NSHE, obo University of Nevada, Reno
Street:1664 North Virginia Street
City:Reno
State:NV
ZIP:89557-0001
County:Reno
Country:US
Cong. District:02

Abstract at Time of Award

CPS:Small: Real-time, Simulation-based Planning and Asynchronous Coordination for Cyber-Physical Systems This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The objective of this research is to investigate how to replace human decision-making with computational intelligence at a scale not possible before and in applications such as manufacturing, transportation, power-systems and bio-sensors. The approach is to build upon recent contributions in algorithmic motion planning, sensor networks and other fields so as to identify general solutions for planning and coordination in networks of cyber-physical systems. The intellectual merit of the project lies in defining a planning framework, which integrates simulation to utilize its predictive capabilities, and focuses on safety issues in real-time planning problems. The framework is extended to asynchronous coordination by utilizing distributed constraint optimization protocols and dealing with inconsistent state estimates among networked agents. Thus, the project addresses the frequent lack of well-behaved mathematical models for complex systems, the challenges of dynamic and partially-observable environments, and the difficulties in synchronizing and maintaining a unified, global world state estimate for multiple devices over a large-scale network. The broader impact involves the development and dissemination of new algorithms and open-source software. Research outcomes will be integrated to teaching efforts and undergraduate students will be involved in research. Underrepresented groups will be encouraged to participate, along with students from the Davidson Academy of Nevada, a free public high school for gifted students. At a societal level, this project will contribute towards achieving flexible manufacturing floors, automating the transportation infrastructure, autonomously delivering drugs to patients and mitigating cascading failures of the power network. Collaboration with domain experts will assist in realizing this impact.

Publications Produced as a Result of this Research

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Marble J, Bekris KE. "Asymptotically Near-Optimal Planning with Probabilistic Roadmap Spanners" IEEE Transactions on Robotics, v.29, 2013, p.432.

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