  This paper studies the cooperative source seeking problem via a networked
multi-vehicle system. In contrast to existing literature, the multi-vehicle
system is controlled to the source position that maximizes aggregated multiple
unknown scalar fields and each sensor-enabled vehicle only samples measurements
of one scalar field. Thus, a single vehicle is unable to localize the source
and has to cooperate with its neighboring vehicles. By jointly exploiting the
ideas of the consensus algorithm and the stochastic extremum seeking (ES), this
paper proposes novel distributed stochastic ES controllers, which are
gradient-free and do not need any absolute information, such that the
multi-vehicle system simultaneously approaches the source position. The
effectiveness of the proposed controllers is proved for quadratic scalar
fields. Finally, illustrative examples are included to validate the theoretical
results.
