Dynamic Task Planning of Aerial Robotic Platforms for Ground Sensor Data Collection and Processing

The adoption of wireless sensor network systems is becoming widespread in critical large-scale monitoring applications. These include but are not limited to pipeline infrastructures for oil and water, border areas, roads and railway systems. In such scenarios, airborne robotic platforms like unmanned aerial vehicles (UAVs) can provide valuable services for data collection, communication relaying and higher level supervision. This the case for both single UAV deployment as well as for swarms of UAVs collaboratively integrated into the monitoring system. The paper discusses the opportunity for in-network pre-processing of sensor data for local UAV task planning in order to increase the efficiency of the data collection process. A gradient scheme is introduced for decision support of the UAV task planning. The results are validated by simulation.