Untethered, underwater sensors, deployed for event detection and tracking and operating in an autonomous mode will be required to self-assemble into a configuration, which optimizes their coverage, effectively minimizing the probability that an event in the target area goes undetected. This organized, cooperative, and autonomous, spreading-out of the sensors is complicated due to sensors localized communication. A given sensor will not in general have position and velocity information for all sensors, but only for those in its communication area. A possible approach to this problem, motivated by an evolutionary optimization technique, Particle Swarm Optimization (PSO) is proposed and extended in a novel way. A distributed version of PSO is developed. A distributed version of PSO is explored using experimental fitness to address the coverage problem in a two dimensional area.
Date of creation, presentation, or exhibit
Department, Program, or Center
Microelectronic Engineering (KGCOE)
Tillett, Jason; Rao, Raghuveer; and Sahin, Ferat, "A Distributed evolutionary algorithmic approach to the coverage problem for submersible sensors" (2004). Accessed from
RIT – Main Campus