A Robust LiDAR-Based Indoor Exploration Framework For UAVs in Uncooperative Environments

This paper introduces a robust frame-work for autonomous exploration using UAVs in uncooperative indoor environments, i.e. destroyed, unknown, and with limited visibility. The proposed system integrates a LiDAR-based Simultaneous Localization and Mapping (SLAM) algorithm, a Euclidian/Truncated Signed Distance Field (E/TSDF) mapping approach, a frontier-based exploration logic, a B-Spline motion planner, and a parallel Collision Avoidance (CA) module to ensure safe and efficient navigation through unexplored areas in real-time. Successful validation in simulated environments demonstrates the system's robustness in handling real-world issues such as odometry uncertainty, depleted point clouds, and intermittent networking in distributed setups.