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Talk-14: Sensor-Driven Area Coverage for an Autonomous Unmanned Aerial Vehicle using MOOS

Liam Paull, Carl Thibault, Amr Nagaty, Mae Seto and Howard Li, University of New Brunswick, Defence Research and Development Canada (DRDC)

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are suited for larger scale area surveys as they cover ground quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage challenging. Previous area coverage planning was offline and assume the UAV follows the planned trajectory exactly. In this work, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft can plan paths in-situ based on sensor data and a model of the coverage camera. An information theoretic methodology selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept developed for autonomous underwater vehicles is extended to UAVs and ensures the UAV achieve their global coverage mission.

UAV state data is transmitted through a wireless link to the ground control station (GCS). Control decisions are made on the GCS and uploaded as heading reference values to the UAV where they are tracked by the inner on-board control loop. The GCS runs the MOOS middleware and uses the IvP multi-objective piecewise optimization framework to reconcile behaviors at run-time. The GCS/MOOS Interface connects to the UAV through a wireless UDP link and can receive state data and send the desired headings, reconciled by the IvP optimization, directly to the UAV. The IvP Helm performs the multi-objective IvP optimization using the new behaviors BHV_Information_Gain and BHV_Branch_Entropy. Hardware-in-the-loop simulations and implementation on a UAV validates the method's effectiveness.

Categories:

  • Unmanned Aerial Vehicles (UAVs)
  • MOOS-IvP
  • IvP Behaviors
  • Payload Autonomy Interface