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Distributed Sensing, Control, and Uncertainty (Maryland Overview)

Distributed Sensing, Control, and Uncertainty (Maryland Overview). P. S. Krishnaprasad University of Maryland, College Park Department of Electrical and Computer Engineering &

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Distributed Sensing, Control, and Uncertainty (Maryland Overview)

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  1. Distributed Sensing, Control, and Uncertainty (Maryland Overview) P. S. Krishnaprasad University of Maryland, College Park Department of Electrical and Computer Engineering & Institute for Systems Research ------------ Center for Communicating Networked Control Systems ARO-MURI01 Review Meeting Boston University October 20-21, 2003

  2. Outline Maryland Team Maryland Infrastructure (Labs, Test-beds) Educational Activities (undergraduate, graduate, post-doctoral) Overall Goals of the Center Maryland Program Research Education Outreach and Transition Synergy within Team Research in distributed sensing, control, and uncertainty

  3. Maryland Team Faculty: John Baras, Dimitrios Hristu-Varsakelis, Eric Justh, P. S. Krishnaprasad, Prakash Narayan Research Associates: Babak Azimi-Sadjadi (also Research Assistant Professor at RPI), and Amir Handzel (part-time), now at Beyond Genomics. Also Xiaobo Tan has been involved in some aspects of the project as a research associate supported by John Baras on non-MURI funds. 7 Graduate Students supported, and 2 associated 4 undergraduate students supported/associated Recent ARL Collaboration: Mikhail Vorontsov (optics) Other recent ARL Interactions: Tien Pham, Michael Scanlon, and Stuart Young (acoustics/robotics)

  4. Maryland Infrastructure Intelligent Servosystems Laboratory (ISL) Intelligent Control Engineering Laboratory (ICEL) Systems Engineering and Integration Laboratory (SEIL) ISL focuses on control, signal processing, interacting cooperative smart systems (principles and technology), biologically inspired approaches to networked systems ICEL focuses on networked control experiments SEIL focus includes networking, signal processing

  5. Binaural robots Maryland Infrastructure Wireless networked robots equipped with auditory, sonar, GPS and vision capabilities.Test-bed for exploration of advanced on-board and off-board algorithms DGPS vehicles Other robots equipped with laser range finder, compass, GPS etc.

  6. Educational Activities REU (3), MERIT (2), MURI (4) projects for undergraduates GPS-robot; formations with peer-to-peer communication; acoustic localization from bearings; MDLe implementation; stabilization over networks; and steering laws for obstacle avoidance. M.S. thesis in Independent Component Analysis (ICA) completed (Yu Mao), and one nearing completion (Bijan Afsari). Ph.D thesis of Sean Andersson (on sensing and control) completed. Ph.D work in Formations, Distributed Control, Inertial Sensing, Channel (RF and optical) modeling, Stochastic Control (5) Two high school interns - summer and fall 2003

  7. Overall Goals of the Center Build foundations and tools for effective integration of control, communication, and signal processing technologies • Cope with noisy, limited number of shared (sensor-actuator) • channels via • Coding and modulation for feedback control • Protocols for access control and transmission control • tailored to maximize quality of service (QoS) • Signal processing and feedback control methods for • distributed reduction of uncertainty in sensor fields • Development of algorithmic frameworks for on-board • and off-board computation and control in dynamic, • mobile nodes of distributed systems

  8. Maryland Program (Research) Illustrations of motivating problems • Principles of organization of teams of UAVs and UGVs can arise from an understanding of biological sensory processing (e.g. audition), and control (e.g. swarming) • Free space optical links for high data rate communication of images is an emerging technology. Networks based on such links pose new questions and opportunities Uncertainty arising from atmospheric turbulence Feedback from remote user leading to re-direction of sensors • Acoustic/seismic/RF sensor fields for distributed data gathering and the use of advanced (biologically-inspired) algorithms for self-organization, routing and signal processing over networks of such sensors

  9. Maryland Program (Research) Networks, UAV’s and UGV’s From NRC study (2000), NMAB-495

  10. Maryland Program (Research) Distributed Sensor Fields Photo: courtesy of Michael Scanlon, ARL

  11. Maryland Program (Research) • Distributed sensing, control, and uncertainty: Bio-mimetic Methods • for Acoustic Source Localization(P. S. Krishnaprasad) • Swarms, curvature and convergence (E. Justh) • Multi-user estimation (B. Azimi-Sadjadi) • Collaborative control of moving agents under communication and • functionality constraints (J. S. Baras) • Reliable communication over time-varying RF and optical fading • channels (P. Narayan) • Distributed optimization and navigation (D. Hristu-Varsakelis)

  12. Maryland Program (Education) Continuous training of one post-doctoral fellow in the MURI grant Balanced program of research in theoretical foundations and empirical exploration with meaningful test-beds as part of M.S. and Ph.D. level training Continued involvement of undergraduates (from other universities) through NSF-REU and NSF-RITE style programs

  13. Maryland Program (Outreach and Transition) • Build on collaboration with ARL in the area of adaptive optics • Free space optical communication link at ARL for • high speed image transfer and image-based feedback control • Study of (networked) optical communication links • Build on interactions with ARL (also with NRL) in the areas of • UAV’s and UGV’s collaborating with ground/soldier sensors • Unattended ground sensor + soldier helmet signal processing • Develop collaboration with IAI (Vikram Manikonda) & NRL • (Jeff Heyer, Larry Schuette and Eric Justh) IEEE CDC December 2002, 2 special sessions, IEEE CDC December 2003, workshop on motion control languages

  14. Synergy within Team • Long-standing collaborations with Harvard and Boston • Universities on smart systems, adaptive optics etc. • New collaboration between Illinois and Maryland • (Hristu-Varsakelis and Kumar, IEEE CDC 2002 paper and • journal paper) • Joint work on formal languages for robotics (MDLe), • cooperative control and networked control within ISL • and in collaboration with Harvard to be extended to BU. • Collaboration on optical links (Krishnaprasad and Narayan) • with joint Ph.D. student (Arash Komaee) • Joint work on communication networks within CSHCN • and SEIL (major industrial program) • Other leveraged resources include NASA, MURI97, • AFOSR, NRL, ATIRP/CTA, and NSF-REU...

  15. END OF OVERVIEW OF UMD EFFORT

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