AUSPEX: An integrated open-source decision-making framework for UAVs in rescue missions

Unmanned aerial vehicles (UAVs) have become paramount for search and rescue (SAR) missions due to their ability to access hazardous and challenging environments and to rapidly provide cost-effective aerial situational awareness. Nevertheless, current UAV systems are designed for specific tasks, often focusing on benchmarking use cases. Therefore, they offer limited adaptability for the diverse decision-making demands of SAR missions. Furthermore, commercially available integrated UAV systems are non-open-source, preventing further extension with state-of-the-art decision-making algorithms. In this paper, we introduce Automated Unmanned Aerial Swarm System for Planning and EXecution (AUSPEX), which is a holistic, modular, and open-source framework tailored specifically for enhancing the decision-making capabilities of UAV systems. AUSPEX integrates diverse capabilities for knowledge representation, perception, planning, and execution with state-of-the-art decision-making algorithms. Additionally, AUSPEX considers the heterogeneity of available UAV platforms and offers the possibility of including off-the-shelf and generic UAVs, with an open architecture into the AUSPEX ecosystem. The framework relies only on open-source components to ensure transparency, as well as system scalability and extensibility. We demonstrate AUSPEX's integration with the Unreal Engine-based simulation framework REAP for software-in-the-loop validation and a platform-independent graphical user interface (AUGUR). We demonstrate how AUSPEX can be used for generic scenarios in SAR missions while highlighting its potential for future extensibility.