Prof. João P. Hespanha Profile

Prof. João P. Hespanha

Professor at Univ of California Santa Barbara

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Publications (8)

Proceedings Article | 17 May 2013 Paper

Learning consensus in adversarial environments

Kyriakos Vamvoudakis, Luis García Carrillo, João Hespanha

Proceedings Volume 8741, 87410K (2013) https://doi.org/10.1117/12.2014372

KEYWORDS: Information security, Network security, Systems modeling, Neural networks, Control systems, Defense and security, Silver, Nickel, Rhodium, Neurons

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Proceedings Article | 24 May 2012 Paper

Autonomous UAV persistent surveillance using bio-inspired strategies

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Jason Isaacs, Sriram Venkateswaran, Tien Pham

Proceedings Volume 8389, 838917 (2012) https://doi.org/10.1117/12.920018

KEYWORDS: Unmanned aerial vehicles, Sensors, Sensor networks, Acoustics, Biomimetics, Data communications, Surveillance, Unattended ground sensors, Source localization, Environmental sensing

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Proceedings Article | 23 May 2011 Paper

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Tien Pham

Proceedings Volume 8047, 80470Y (2011) https://doi.org/10.1117/12.882802

KEYWORDS: Sensors, Unmanned aerial vehicles, Acoustics, Sensor networks, Biomimetics, Source localization, Digital filtering, Unattended ground sensors, Algorithm development, Signal to noise ratio

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A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Proceedings Article | 8 May 2010 Paper

Heterogeneous sensor networks: a bio-inspired overlay architecture

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Daniel Klein, Jason Isaacs, Sriram Venkateswaran, Tien Pham

Proceedings Volume 7694, 76940T (2010) https://doi.org/10.1117/12.851533

KEYWORDS: Sensors, Unmanned aerial vehicles, Acoustics, Sensor networks, Biomimetics, Source localization, Cameras, Unattended ground sensors, Telecommunications, Bacteria

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Proceedings Article | 5 May 2009 Paper

Heterogeneous sensor networks: a bio-inspired overlay architecture

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Daniel Klein, Tien Pham, Ananthram Swami

Proceedings Volume 7333, 73330E (2009) https://doi.org/10.1117/12.819221

KEYWORDS: Sensors, Source localization, Biomimetics, Sensor networks, Unattended ground sensors, Unmanned aerial vehicles, Algorithm development, Acoustics, Databases, Signal to noise ratio

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Proceedings Article | 5 May 2009 Paper

GeoTrack: bio-inspired global video tracking by networks of unmanned aircraft systems

Prabir Barooah, Gaemus Collins, João Hespanha

Proceedings Volume 7321, 73210F (2009) https://doi.org/10.1117/12.820490

KEYWORDS: Detection and tracking algorithms, Video, Sensors, Video processing, Algorithm development, Error analysis, Global Positioning System, Video surveillance, Cameras, Sensor fusion

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Proceedings Article | 19 September 2001 Paper

Simulation and modeling for military air operations

Ruth Kreichauf, Saad Bedros, Yusuf Ateskan, Joao Hespanha, Hakan Kizilocak

Proceedings Volume 4367, (2001) https://doi.org/10.1117/12.440038

KEYWORDS: Control systems, Device simulation, Radar, Monte Carlo methods, Systems modeling, Computer architecture, Human-machine interfaces, Sensors, Computer simulations, Feedback control

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Proceedings Article | 31 May 1996 Paper

Toward the supervisory control of families of nonlinear regulators

Joao Hespanha, A. Morse

Proceedings Volume 2715, (1996) https://doi.org/10.1117/12.240791

KEYWORDS: Process modeling, Error analysis, Adaptive control, Switching, Logic, Dynamical systems, Signal generators, Complex systems, Feedback control, Signal processing

Showing 5 of 8 publications

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