DWA-3D: A reactive planner for robust and efficient autonomous UAV navigation in confined environments

Abstract

Despite the growing impact of Unmanned Aerial Vehicles (UAVs) across various industries, most of the current available solutions lack a robust autonomous navigation system to deal with the appearance of obstacles safely. This work presents an approach to perform autonomous UAV planning and navigation in indoor or confined scenarios where a safe and high maneuverability is required, due to the cluttered environment and narrow rooms. The system combines an RRT* global planner with a newly proposed reactive planner, DWA-3D, which is an extension of the well-known DWA method for 2D robots. We provide a theoretical-empirical method for adjusting the parameters of the objective function to optimize, which eases the classical difficulty for tuning them. An onboard LiDAR provides a 3D point cloud, which is projected on an OctoMap in which the planning and navigation decisions are made. There is not a prior map; the system builds and updates the map online, from the current and the past LiDAR information included in the OctoMap. Extensive real-world experiments were conducted to validate the system and to obtain a fine-tuning of the involved parameters. These experiments allowed us to provide a set of values that ensure safe operation across all the tested scenarios. Just by weighting two parameters, it is possible to prioritize either horizontal path alignment or vertical (height) tracking, resulting in enhancing vertical or lateral avoidance, respectively. Additionally, our DWA-3D proposal is able to navigate successfully even in absence of a global planner or with one that does not consider the drone’s size. Finally, the conducted experiments show that computation time with the proposed parameters is not only bounded but also remains stable at around 40 ms, regardless of the scenario complexity.