UAV Autonomous Indoor Exploration and Mapping for SAR Missions: Reflections from the ICUAS 2022 Competition
Adil Farooq, Antreas Anastasiou, Nicolas Souli, Christos Laoudias, Panayiotis Kolios, Theocharis Theocharides
Abstract
The technological advancement in Unmanned Aerial Vehicles (UAVs) or drones and their deployment in real-life Search and Rescue (SAR) missions is imminent. We, therefore, present a perception-aware autonomous exploration framework aimed at performing vision-based target detection and collision avoidance with an Unmanned Aerial Vehicle (UAV). The UAV utilizes a depth camera for maneuvering and finding the target. The underlying indoor exploration approach considers autonomous collision-free navigation, as well as target detection with a ballistic ball payload delivery without a prior map. Moreover, the proposed method allows safe navigation in enclosed unknown areas congested with randomly positioned obstacles and target locations. Our underlined end-to-end system architecture integrates the proposed exploration strategy. Extensive simulation experiments, using several Key Performance Indicators (KPIs), showcase the effectiveness of the proposed Robot Operating System (ROS) framework in a simulated Gazebo environment under various parameter settings.