Simulation of a cognitive algorithm for a distributed robotic sensing network

This paper presents simulation and analysis of a collective of autonomous unmanned ground-based vehicles navigating a building searching for increasing smoke concentrations. The vehicles communicate smoke concentrations to each other to determine the location of the highest concentration value. The data generated front the robots´ sensors is used to activate a semantic network to generate data for further cognitive operations. Statistical analysis is employed on the data to identify schema and themes, which enable the robots to convey a story of their experiences, thus emulating human episodic memory.