Controlling a fleet of unmanned aerial vehicles (UAVs) to collect uncertain information in a threat environment

摘要

Unmanned aerial vehicles (UAVs) are used to carry out missions that are dangerous and performed deep into enemy territory, making it risky for manned operations. Though UAV technology has advanced, it is expensive. In a recent survey the US Air Force found that crashes of UAVs resulted in a loss of $48 million in 2011. Moreover, such crashes may reveal the embedded technology to the enemies. At present, UAVs are controlled by human operators through either a video data link (VDL) or common data link (CDL). The CDL can help the enemy identify the operator's location and can also be interrupted by electronic warfare causing the UAV to crash. On the other hand, VDL can be hacked by the enemy and they can get access to sensitive information. UAVs can be used in places where an advanced air defense system is not available to the enemy. This article studies the problem of controlling a fleet of UAVs that collect uncertain information from a set of regions. After detection of the information, the vehicle can decide whether to collect it or not. The article considers a scenario where the vehicles are operated automatically and they maintain radio silence during the mission. The control is decentralized and the decisions are made by the vehicle itself. The information collection can be considered as a search theory problem. The search does not stop after finding the first entity and multiple searchers behave independently to achieve a common goal. Due to uncertain information and lack of communication, each vehicle may not be in a position to predict the other member's behavior during the mission. This makes the problem more complicated since it has to be solved as a time-allocation problem, after determining the routes. This article proposes a region-sharing strategy which assigns multiple vehicles to a region. (38 refs.)