Swarm of robot attacking an acoustic source: detection and trapping
Source identification in a complex environment has a remarkable interest in acoustic and noise-engineering as well as in defence applications. The detection of mobile sources through a swarm of drones used as a set of microphones carriers is proposed in the present paper formulating a new theory to solve the problem. A set of N carriers of sensors, each of them equipped by its own dynamics, moves in the environment and can detect the local acoustic field as an effect of the noise emission of unknown mobile sound-sources. Sound received from the microphones on the carriers is the only detectable signal in the field and the only trace the noise-target releases into the environment. The CAI (Centralized Artificial Intelligence) can use the information coming from the microphones to localize in the best way the source.
The swarm pattern noise-source searching is piloted by the CAI that controls the swarm operation and suggests the best re-localization of the agents and thus of the microphones at each time step, with the aim of localizing and trapping the noisesource in an optimal fashion. The mission is completed when the drones localize and reach the noise target.