Quantitative and Qualitative Assessment of Indoor Exploration Algorithms for Autonomous UAVs (2205.13801v1)

Abstract: Indoor exploration is an important task in disaster relief, emergency response scenarios, and Search And Rescue (SAR) missions. Unmanned Aerial Vehicle (UAV) systems can aid first responders by maneuvering autonomously in areas inside buildings dangerous for humans to traverse, exploring the interior, and providing an accurate and reliable indoor map before the emergency response team takes action. Due to the challenging conditions in such scenarios and the inherent battery limitations and time constraints, we investigate 2D autonomous exploration strategies (e.g., based on 2D LiDAR) for mapping 3D indoor environments. First, we introduce a battery consumption model to consider the battery life aspect for the first time as a critical factor for evaluating the flight endurance of exploration strategies. Second, we perform extensive simulation experiments in diverse indoor environments using various state-of-the-art 2D LiDAR-based exploration strategies. We evaluate our findings in terms of various quantitative and qualitative performance indicators, suggesting that these strategies behave differently depending on the complexity of the environment and initial conditions, e.g., the entry point.