Search

The collaboration of heterogeneous multiple robots has been shown to be capable of significantly enhancing the system redundancy, autonomy, robustness, and so on. However, realizing the collaboration with specific tasks in practice often requires the development of sophisticated mechanisms which are envisioned to exploit distinct benefits of the heterogeneous platforms. Thus, we propose a novel air–ground cooperative framework in this paper for the task of multi-target searching under an unknown urban environment. In particular, a group of unmanned aerial vehicles (UAVs) is employed to operate above the urban area to provide surveillance from a global perspective. Under the guidance of UAVs, multiple teams of unmanned ground vehicles (UGVs) are deployed to conduct the target searching missions. The UAVs’ and UGVs’ searching strategies are devised correspondingly leveraging on their own advantageous features. Finally, an ingenious integration of UAVs’ and UGVs’ searching operations is established by a notion of the upper confidence bound. Simulation results are provided to demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]