NDLI: Semi-autonomous management of multiple ad-hoc teams of UAVs

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2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

Using computational swarm intelligence for real-time asset allocation

Semi-autonomous management of multiple ad-hoc teams of UAVs

Rigorous sensor resource management: Methodology and evolutionary optimization

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Author index

2013 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications

2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications

2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications

Semi-autonomous management of multiple ad-hoc teams of UAVs

Content Provider	IEEE Xplore Digital Library
Author	Loe, R. Maracchion, C. Drozd, A.
Copyright Year	2015
Description	Author affiliation: ANDRO Comput. Solutions, LLC, Rome, NY, USA (Loe, R.; Maracchion, C.; Drozd, A.)
Abstract	A Distributed Battle Manager (DBM) system based on Concurrent MACro Partially Observable Markov Decision Processes (CMAC-POMDP) is proposed to manage multiple competing missions. Implementation details are presented for a semi-autonomous management of multiple ad-hoc teams of UAVs operating under extreme uncertainty in a contested environment. The proposed solution is semi-autonomous since command and control teams perform target confirmation, weapon selection, weapon release, and bomb damage assessment. Our proposed approach decomposes the resource management requirements into specialized mission timelines. There would be one adaptive mission timeline for each system objective, and each timeline would be represented by a POMDP. At any time, the DBM would be controlling multiple concurrent timelines that are competing for system resources. Each timeline is solved independently to obtain the optimal MDP solution parameters. These solution parameters are then combined using linear programming with constraints to obtain a suboptimal system solution. The resulting suboptimal solutions provide satisfactory real-time system performance. Under extreme uncertainty, it is preferable to maximize robustness utilizing an adequately performing solution as opposed to finding an optimal but brittle solution. Performance results of the core CMAC-POMDP algorithm are presented for a system implemented to manage multiple heterogeneous sensors addressing multiple simultaneous threats. This simpler resource management system utilizes the same timeline for all of the threats. Simulations demonstrate better than real-time performance even for large numbers of threats. Furthermore, computational requirements are shown to grow linearly with the number of threats. Extension to multiple simultaneous timelines for the DBM system is straightforward.
Starting Page	1
Ending Page	4
File Size	4123677
Page Count	4
File Format	PDF
e-ISBN	9781467375573
DOI	10.1109/CISDA.2015.7208620
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	suboptimal algorithms Target tracking Weapons management Partially Observable Markov Decision Processes concurrent MDPs Markov processes Sensor systems command and control Timing Planning
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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