Automated Photovoltaic Power Plant Inspection via Unmanned Vehicles

Abstract

This article addresses the design of a fully automated photovoltaic (PV) power plant inspection process by a fleet of unmanned aerial and ground vehicles (UAVs/UGVs). More specifically, we consider the problem of assigning a set of target points to be inspected to a fleet of UAVs/UGVs so as to minimize the overall energy consumption while accounting for the battery degradation and the vehicle deterioration. In order to cope with the combinatorial complexity of the problem, we propose a suboptimal resolution strategy that integrates a graph-theoretic approach for local path planning at the robot level into a market-based approach for task assignment at the fleet level. The resulting coordination scheme is scalable and plug and play, and requires a minimal amount of information exchange between the robots and a central auctioneer, thus allowing the interoperability of different robotic platforms. Extensive numerical analysis via a multiagent simulation software shows the effectiveness of the proposed approach.