This one-year exploratory project focuses on applying the dynamic data driven applications system (DDDAS) approach to achieve optimal interlaced distributed control and distributed measurement with networked mobile actuators and sensors. The application system is on chemical fog concentration reduction or elimination. A group of moving sensors make distributed measurements of the diffusion process to characterize the diffusion process (sniffing), meanwhile, the dynamic data sensed is fed to a group of mobile robots equipped with neutralizer dispensers (spraying) to contain the chemical fog. Fundamental research issues include sensing policy, actuation policy, formation regulation and tracking, and optimal path planning. In this one-year exploratory DDDAS project, the PI specifically attacks the optimal interlaced distributed control and distributed measurement with networked mobile actuators and sensors, which will lay a foundation for characterizing and neutralizing multiple, possibly evolving, chemical sources, on and underground, by a team of ground mobile robots equipped with networked sensors (detectors) and actuators (neutralizers).
The proposed research and educational efforts will have a significant impact on the development of mobile actuator and sensor networks for national security interests, water resources, precision agriculture, ecological and environmental monitoring; the creation of interdisciplinary research and environment; recruiting and retaining engineering students. As a motivating example, imagine that a hostile toxic diffusion source is being released and diffusing with no color and no smell. It is very desirable to send a team of mobile robots to sniff around and, meanwhile, dispatch another team of mobile robots to spray/neutralize the diffusion process. Since these robots are networked via wireless links, thus the name "mobile actuator and sensor networks." It is a hard problem to decide where to sniff and where to spray for each individual mobility node when various constraints exist such as limited battery life and obstacles. This project focuses on optimal interlaced distributed control and distributed measurement with networked mobile actuators and sensors. That is, move sensors for better measurements and in turn, move actuators for better control and neutralization. This project provides a new, unique exciting challenge to push the boundary of emerging distributed control system theories with a clear dynamic data driven flavor.
