Optimal Sampling Patterns for Robotic Environmental Monitoring

Cost-efficient methods and technologies for environmental monitoring is an enabler for holistic decision making and sustainable management of natural resources. The information value from monitoring surveys with robotic sensor platforms such as AUVs and UAVs can increase if domain knowledge is exploited when selecting the sampling locations. We investigate how to maximize the information value of surveys targeting dispersible substances by adjusting the survey pattern in accordance with the direction and strength of the wind or water currents. Samples are acquired with a range of different patterns, deployed in a large number of randomly generated emission scenarios in a Monte Carlo framework. The information value from each survey is used as a performance metric to identify opportune pattern configurations. Among the results is the impact that the orientation of the survey pattern relative to the direction of the wind has on the information value, and that given proper orientation the line spacing can be wider. The results are used to suggest guidelines for robotic environmental monitoring surveys.