Resilient cooperative source seeking of double-integrator multi-robot systems under deception attacks

The resilient cooperative source seeking problem of double-integrator multi-robot systems under \mathbf {d}-local deception attacks is investigated. In this article, we first propose a resilient cooperative control algorithm and present a necessary and sufficient condition for its achievement of resilient consensus. Then, through applying the particle swarm optimization algorithm to the resilient cooperative control algorithm, a resilient cooperative source seeking algorithm is proposed. We show that this algorithm can solve the source seeking problems under \mathbf {d}-local deception attacks with an additional potential of addressing the multiple local extrema case. Finally, the feasibility of the proposed algorithms is illustrated by simulation and experimental results.