Estimation-informed, resource-aware robot navigation for environmental monitoring applications

Abstract

Environmental monitoring of spatially-distributed geo-physical processes (e.g., temperature, pressure, or humidity) requires efficient sampling schemes, particularly, when employing an autonomous mobile agent to execute the sampling task. Many approaches have considered optimal sampling strategies which specialize in minimizing estimation error, while others emphasize reducing resource usage, yet rarely are both of these performance parameters used concurrently to influence the navigation. This work discusses how a spatial estimation process and resource awareness are integrated to generate an informed navigation policy for collecting useful measurement information. We also enable a direct comparison between this informed navigation method and more common approaches using two performance metrics. We show that our informed navigation outperforms these approaches based on performance evaluation as a function of estimation error and resource usage for a useful range of coverage within the sampling area.