AUTHOR=Döschl Björn , Sommer Kai , Kiam Jane Jean 

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

JOURNAL=Frontiers in Robotics and AI

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1583479

DOI=10.3389/frobt.2025.1583479

ISSN=2296-9144

ABSTRACT=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.