Cooperative path planning with unmanned vehicle systems for scalar field reconstruction

Abstract

Recently, the use of unmanned systems has increased considerably in a wide range of applications such as environmental monitoring and disaster response operations. Scalar field reconstruction is often an important task in these applications, e.g., temperature and chemical distributions can be modeled as scalar field maps. The field information is initially unknown and unmanned vehicles can be used to gather samples and reconstruct the scalar field. Path planning is important for improving the quality of the reconstruction results, so this study focuses on informative path planning to design an effective and efficient sampling path for scalar field reconstruction. Field reconstruction missions are achieved via cooperation between an unmanned surface vehicle (USV) and an unmanned aerial vehicle (UAV). The data sampled during the task are used to adaptively re-plan the paths of the two vehicles. Cooperation is considered by assuming that the USV is capable of carrying and deploying the UAV. The feasibility of the proposed informative path planning process with USV-UAV cooperation is demonstrated based on the results of numerical simulations.