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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:WAYNE STATE UNIVERSITY
Doing Business As Name:Wayne State University
PD/PI:
  • Marco Brocanelli
  • (614) 599-1671
  • brok@wayne.edu
Award Date:01/13/2020
Estimated Total Award Amount: $ 175,000
Funds Obligated to Date: $ 175,000
  • FY 2020=$175,000
Start Date:02/01/2020
End Date:01/31/2022
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CRII: CSR: Energy-Aware Coordination and Management of Multi-Purpose Autonomous Robots for Maintained Continuity of Operations and Long Battery Lifetime.
Federal Award ID Number:1948365
DUNS ID:001962224
Parent DUNS ID:001962224
Program:CSR-Computer Systems Research
Program Officer:
  • Matt Mutka
  • (703) 292-7344
  • mmutka@nsf.gov

Awardee Location

Street:5057 Woodward
City:Detroit
State:MI
ZIP:48202-3622
County:Detroit
Country:US
Awardee Cong. District:13

Primary Place of Performance

Organization Name:Wayne State University
Street:5057 Woodward Ave
City:Detroit
State:MI
ZIP:48202-3622
County:Detroit
Country:US
Cong. District:13

Abstract at Time of Award

Autonomous Robot (AR) fleets will soon assist humans for the execution of several tasks. One of the most important factors that will likely affect the widespread adoption of AR fleets in our society is their ease of management for the end users. The goal of this project is to achieve the easy management of the AR fleet by allowing end users to indicate the set of tasks to execute during a working period and by implementing algorithms that automatically (i) allocate tasks to ARs, (ii) coordinate recharge schedules, (iii) ensure continuity of operations, and (iv) minimize the battery degradation. The intellectual merits of this project are focused on designing an AR fleet manager system that can be used by end users to interact easily with an AR fleet. Three main research thrusts are: (i) joint optimization of concurrent tasks allocation and recharge scheduling for ARs to minimize the task downtime and battery degradation during the working period; (ii) coordination of the ARs' computing and sensing resources to balance tasks performance and energy consumption; (iii) full system implementation and experimentation on a small-scale physical testbed and a large-scale simulated testbed. The proposed work will introduce new technologies available for the management of AR fleets and boost the widespread use of autonomous robots in our society, e.g., homes, smart farms, industry, and smart cities. The project will provide a new hardware and software testbed to help train and inspire undergraduate and graduate students. New industry collaborations will be established to enhance AR adoption. New academic collaborations will also be established with researchers in various areas including robotics, artificial intelligence, control systems, sensing, and approximation algorithms. All the new algorithms and the experimental results generated as part of the proposed project will be distributed in the form of journal articles, conference proceedings, workshops, invited presentations, and student thesis. In addition, the data, source code, simulators, and hardware details will be maintained on a dedicated research website (http://brok.eng.wayne.edu/AFM.html). This repository will be retained and maintained for at least five years after the completion of the project. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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