Decentralised Multi-UAV Cooperative Searching Multi-Target in Cluttered and GPS-Denied Environments

In recent years, the use of multi-unmanned aerial vehicles (UAVs) systems in outdoor GPS enabled environments has increased significantly. Their use in GPS-denied environments, however, is still a complex task. Examples of such environments include search and rescue inside buildings or collapsed building scenarios, urban or natural canyons, in which the GPS signal is limited or blocked. In order to provide a possible solution for these applications, this paper presents a multi-UAV system that can be utilised for a team of UAVs to autonomously navigate, search and detect multiple targets in a cluttered and GPS-denied environment. The multi-UAV system uses a decentralised framework based on Decentralised Partially Observable Markov Decision Processes (Dec-POMDP) to formulate the decision-making process considering uncertainties in the environments and sensing. This system was designed for a mission that needs to cooperate efficiently to search and find multiple targets, without knowing possible locations, by sharing limited vital observations through WiFi connection. The system was tested in several cluttered and GPS-denied environments simulated in Gazebo and ROS interface. The environments were populated with different numbers and types of obstacles, several targets, a team of UAVs and boundaries. After comparing three different searching strategies, the results show that the system is capable of cooperatively searching and finding multiple targets in an effective approach while without having a collision in a complex environment. The multi-UAV system is robust to uncertainties in target exploration and localisation, enabling the use of multiple UAVs to enhance critical missions for challenging scenarios such as search and rescue or exploration and disaster management and assessment.