Efficient environmental monitoring using cost-aware path planning

This paper presents an efficient environmental monitoring strategy that considers the information gain along the trajectory of a robot. In order to monitor environmental parameters such as temperature and chemical concentration, an estimation method based on Gaussian process regression is used. The goal of this paper is to model accurate spatio-temporal phenomena by reducing the uncertainty over the surveillance region. A cost-aware path planning based environmental monitoring is desirable for mobile sensor networks since robots are coordinated to follow a trajectory with the maximum accumulated information gain, as well as the traveling distance. The proposed method with respect to different sampling methods is demonstrated in simulations.