Multi-AAV Formation Search Using Variable Resolution Cognitive Map and Tree-Type Topologies Under Limited Sensing Environments

Cooperative search is a fundamental task for the autonomous aerial vehicles (AAVs), and cognitive maps are necessary resources for the entire search process. However, due to the limited sensing range of an individual AAV, it naturally throws a tradeoff between the coverages and connectivity maintenance for the specific search implementations. A simple but efficient way to address this problem is to apply the formations. However, traditional methods using fixed formation structures and constant resolution maps are insufficient to improve the global search performances, due to their lack of adaptabilities and flexibilities. This article proposes a novel method for the AAV formation searches that is based on the variable resolution cognitive map (VRCM) and the multibranch tree (MBT) communication topology. The VRCM aims to establish the cognitive maps with different map resolutions to support the various search behaviors. An incremental Gaussian process model is applied for the VRCM constructions, such that the behavioral diversity and search flexibility can be improved during the online manipulations. The MBT topologies are used to interconnect the AAVs where the root node is the formation leader that is capable of the plannings of the global search paths. A reconfiguration scheme based on the cognitive maps and benchmark formations is provided to optimize the coverage performance of the AAV formations. Simulation results demonstrate the advantages of the proposed method on the stability of switching formations, search accuracy, coverage efficiency, and retrospect behaviors to the areas with high target occurrences.