1. Distributed Sensing, Control, and Uncertainty
(Maryland Accomplishments)
P. S. Krishnaprasad
University of Maryland, College Park
Department of Electrical and Computer Engineering
&
Institute for Systems Research
Center for Communicating Networked Control Systems
Presentation Slides for ARO Management
July 1, 2003

2. Objectives
Build foundations and tools for effective integration of control,
communication, and signal processing technologies based on:
coping with noisy, limited number of shared (sensor-actuator)
channels via (a) coding and modulation for feedback control;
(b) protocols for access control; (c) signal processing and feedback
control for distributed reduction of uncertainty in sensor fields;
(d) development of algorithmic frameworks for on-board and off-
board computation in dynamic mobile nodes of distributed systems

3. Development and implementation of a platform-independent
Accomplishments
Development and implementation of a platform-independent
language MDLe for distributed, mobile, sensor platform motion
control. Demonstration of controlled acoustic sensing activities
under MDLe. Development of new platform coordination
algorithms. GPS-in-the-loop feedback control.
Successful development of new particle filters for state tracking,
and change detection.
Advancing dynamic sound source localization using biological
principles with applications to distributed acoustic sensors.
Stochastic models for communication channels (optical physics,
quantization, and learning).
Distributed and asynchronous control subject to communication
constraints - new theory and algorithms
MDLe has been distributed to multiple research groups. A proposed tutorial workshop at the IEEE Conference on Decision and Control in December 2003 will devote a significant portion of the allotted time to exposing this work.
The sound source localization algorithms have been presented and demonstrated to researchers at the Army Research Lab (ARL) in Adelphi, MD.
Ongoing work on optical free-space channels has potential applications to a testbed at ARL.
Work on UAV coordination algorithms has been demonstrated in a ground vehicle testbed at the Naval Research Lab before eventual transitioning to an air vehicle testbed,

4. Upper right panel shows a carrier-sense differential GPS equipped mobile robot that serves as a platform for testing our MDLe language implementation and for demonstration of safe navigation algorithms. Upper left panel displays simulation results from our distributed cooperative control algorithms used in guiding a team of mobile robots through a succession of way-points. The algorithms are applicable to small, unmanned aerial vehicles (UAVs) equipped with steering control auto-pilots. The lower left panel presents the signature curves associated to (multiple) broad band sound sources used in the guidance of robots such as the one on the lower right panel equipped with a binaural head (mounted with two sensitive microphones).
Some of the work on UAV algorithms has been partially supported by other grants from NRL and AFOSR.