Multi-robot System Cooperative Source Seeking Under False Data Injection Attack
This paper focuses on the cooperative source seeking problem of multi-robot system,that is,by driving multiple robots to cooperate with each other to seek the location of the physical signal emitter in the unknown en-vironment.Due to the fact that robots executing tasks are usually in an outdoor open network environment,false data injection attacks generated by attackers can easily lead to the failure of source seeking tasks in multi-robot sys-tem.In order to still seek the source in the situation of network attacks,this paper proposes a cooperative multi-di-mensional source seeking method for multi-robot system based on resilient vector convergence.Unlike existing liter-ature that decomposes vectors into scalars on various dimensions when dealing with multi-dimensional source seek-ing,scalar based resilient convergence protocols are designed.The multi-dimensional source seeking method pro-posed in this paper not only effectively resists false data injection attacks,but also defines a more rigorous and ac-curate security interval compared to security intervals of traditional scalar information.Under the assumption of f-locally bounded false data injection attack model,theoretical analysis provides sufficient and necessary conditions for normal robots to seek the source point under the designed control protocol.The simulation results show that the proposed method has superiority in cooperative source seeking and resistance to false data injection attacks in dis-tributed multi-robot system.
万方数据
维普
