Abstract
Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the autonomy of the vehicle and reduce the operator workload. These automated mission planning and replanning systems require a Human Computer Interface (HCI) that facilitates the visualization and selection of plans that will be executed by the vehicles. In addition, most missions should be assessed before their real-life execution. This paper extends QGroundControl, an open-source simulation environment for flight control of multiple vehicles, by adding a mission designer that permits the operator to build complex missions with tasks and other scenario items; an interface for automated mission planning and replanning, which works as a test bed for different algorithms, and a Decision Support System (DSS) that helps the operator in the selection of the plan. In this work, a complete guide of these systems and some practical use cases are provided.
Highlights
The use of Unmanned Aerial Vehicles (UAVs), referred to as drones, has highly increased in the last decade, becoming very popular in many applications including traffic monitoring [1], agriculture [2] or disaster and crisis management [3], since they avoid risking human lives while their manageability permits reaching areas that are hard to access
QGroundControl [9], an open-source ground control station simulator, has been extended by adding an automated planning interface, so this framework can work as a test bed for mission planning and replanning algorithms, and for decision making methods
This paper provides an extension of QGroundControl, providing this test bed and all the lacking capabilities mentioned
Summary
The use of Unmanned Aerial Vehicles (UAVs), referred to as drones, has highly increased in the last decade, becoming very popular in many applications including traffic monitoring [1], agriculture [2] or disaster and crisis management [3], since they avoid risking human lives while their manageability permits reaching areas that are hard to access. Due to the complexity and multiple conflicting objectives of this problem, several non-dominated solutions (i.e., the Pareto Optimal Frontier (POF)) are obtained This situation hinders the process of decision making for the operator when selecting the final plan. QGroundControl [9], an open-source ground control station simulator, has been extended by adding an automated planning interface, so this framework can work as a test bed for mission planning and replanning algorithms, and for decision making methods. This extension allows operators to automatically plan a mission, simulate this plan and perform a replanning during the execution.
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