Award Abstract # 1849198
S&AS: INT: COLLAB: Aerodynamic Intelligent Morphing System (A-IMS) for Autonomous Smart Utility Truck Safety and Productivity in Severe Environments

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: GEORGIA TECH RESEARCH CORP
Initial Amendment Date: April 19, 2019
Latest Amendment Date: March 27, 2025
Award Number: 1849198
Award Instrument: Standard Grant
Program Manager: James Donlon
jdonlon@nsf.gov
 (703)292-8074
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: May 1, 2019
End Date: September 30, 2025 (Estimated)
Total Intended Award Amount: $325,000.00
Total Awarded Amount to Date: $325,000.00
Funds Obligated to Date: FY 2019 = $325,000.00
History of Investigator:
  • Kyriakos G Vamvoudakis (Principal Investigator)
    kyriakos@gatech.edu
Recipient Sponsored Research Office: Georgia Tech Research Corporation
926 DALNEY ST NW
ATLANTA
GA  US  30318-6395
(404)894-4819
Sponsor Congressional District: 05
Primary Place of Performance: Georgia Institute of Technology
225 North Avenue, NW
Atlanta
GA  US  30332-0001
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): EMW9FC8J3HN4
Parent UEI: EMW9FC8J3HN4
NSF Program(s): S&AS - Smart & Autonomous Syst
Primary Program Source: 01001920DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9150, 046Z
Program Element Code(s): 039Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Utility trucks are the first responders in areas of extreme weather situations for tasks such as rescuing people from disaster areas, cutting trees to restore traffic, and repairing electric posts and restoring power. This study establishes a scientific framework for maintaining the productivity and safety of emergency response vehicles while eliminating accidents. This is implemented via a novel integrated framework to monitor and predict weather conditions and feed that information into intelligent mechanisms that autonomously shape the aerodynamic surfaces of utility trucks. The project includes recruitment efforts and activities to integrate high-school students, as well as students from multiple cultures, and disciplines into autonomy research. This project is expected to contribute new scientific knowledge and engineering techniques for next generation transportation infrastructure resiliency, and to facilitate economic growth in the state of Alabama.

Unlike conventional approaches, the A-IMS will integrate model-free shape-morphing learning mechanisms with model-based interactive design to manage air-fluid flows, based on the road conditions, meteorology, speed limit, wind speed, and direction. This potentially transformative framework for A-IMS will: (1) bring new perspectives of learning to enhance the adaptability and intelligence in natural-engineering systems that leverage physical and information processes; (2) establish an integrated design framework for hazardous environments to achieve resilience, and productivity through integrated adaptation of morphological properties while also mitigating the effects of potentially adversarial learning agents that can exist in the cloud; (3) investigate the interactive physical components of the A-IMS, that will simultaneously operate in two different mediums of multi-phase fluids, and solids (i.e., the air/fluid and road). The A-IMS framework will be evaluated through hardware/software implementation, as well as in real-world conditions in the unique test conditions available at Wall of Wind at Florida International University. The project's education and outreach component include integrated research and education plans that will lead to technology transfer and summer camps with a special focus on reaching out to underrepresented minorities and women.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 39)
Zhai, Lijing and Kanellopoulos, Aris and Fotiadis, Filippos and Vamvoudakis, Kyriakos G. and Hugues, Jerome "Towards Intelligent Security for Unmanned Aerial Vehicles: A Taxonomy of Attacks, Faults, and Detection Mechanisms" Proc. AIAA SCITECH 2022 Forum , 2022 https://doi.org/10.2514/6.2022-0969 Citation Details
Zhai, Lijing and Fotiadis, Filippos and Vamvoudakis, Kyriakos G. and Hugues, Jérôme "Timing-Aware Resilience of Data-driven Off-policy Reinforcement Learning for Discrete-Time Systems" 2023 American Control Conference (ACC) , 2023 https://doi.org/10.23919/ACC55779.2023.10155865 Citation Details
Zhai, Lijing and Vamvoudakis, Kyriakos G. "A Data-Based Moving Target Defense Framework for Switching Zero-Sum Games" 2021 IEEE Conference on Control Technology and Applications (CCTA) , 2021 https://doi.org/10.1109/CCTA48906.2021.9659196 Citation Details
Zhai, Lijing and Vamvoudakis, Kyriakos_G "A databased private learning framework for enhanced security against replay attacks in cyberphysical systems" International Journal of Robust and Nonlinear Control , v.31 , 2020 https://doi.org/10.1002/rnc.5040 Citation Details
Zhai, Lijing and Vamvoudakis, Kyriakos G. and Hugues, Jerome "A Graph-Theoretic Security Index Based on Undetectability for Cyber-Physical Systems" 2022 American Control Conference (ACC) , 2022 https://doi.org/10.23919/ACC53348.2022.9867294 Citation Details
Zhai, Lijing and Vamvoudakis, Kyriakos G. and Hugues, Jerome "Switching Watermarking-based Detection Scheme Against Replay Attacks" 2021 IEEE Conference on Decision and Control , 2021 https://doi.org/10.1109/CDC45484.2021.9683652 Citation Details
Chakrabarty, Ankush and Jha, Devesh K. and Buzzard, Gregery T. and Wang, Yebin and Vamvoudakis, Kyriakos G. "Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation" IEEE Transactions on Neural Networks and Learning Systems , 2020 https://doi.org/10.1109/TNNLS.2020.2978805 Citation Details
Fotiadis, Filippos and Kanellopoulos, Aris and Vamvoudakis, Kyriakos G. "Constrained Differential Games for Secure Decision-Making Against Stealthy Attacks" 2020 American Control Conference (ACC) , 2020 10.23919/ACC45564.2020.9147555 Citation Details
Fotiadis, Filippos and Vamvoudakis, Kyriakos G. "Recursive Reasoning for Bounded Rationality in Multi-Agent Non-Equilibrium Play Learning Systems" 2021 IEEE Conference on Control Technology and Applications (CCTA) , 2021 https://doi.org/10.1109/CCTA48906.2021.9658965 Citation Details
Fotiadis, Filippos and Vamvoudakis, Kyriakos. G. "Concurrent Receding Horizon Control and Estimation against Stealthy Attacks" IEEE Transactions on Automatic Control , 2022 https://doi.org/10.1109/TAC.2022.3195922 Citation Details
Fotiadis, Filippos and Vamvoudakis, Kyriakos. G. "Learning-Based Actuator Placement for Uncertain Systems" 2021 IEEE Conference on Decision and Control , 2021 https://doi.org/10.1109/CDC45484.2021.9683690 Citation Details
(Showing: 1 - 10 of 39)

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