DWA-3D: A Reactive Planner for Robust and Efficient Autonomous UAV Navigation

2024-09-09

arXiv.org

AI Summary

Unmanned aerial vehicles (UAVs) lack safe, real-time autonomous obstacle avoidance in complex, confined 3D environments. Method: This paper proposes a mapless online 3D navigation framework integrating RRT* for global planning and a novel three-dimensional Dynamic Window Approach (DWA-3D)—the first theoretically grounded and practically implemented extension of DWA to 3D space. It introduces a theory–empiricism co-driven cost-function parameter tuning strategy, enables fully reactive navigation using DWA-3D alone, and employs a dual-weight mechanism to flexibly prioritize lateral versus longitudinal obstacle avoidance. Real-time Octomap construction and dynamic obstacle updating are performed onboard using 3D LiDAR. Results: The system achieves stable single-frame computation time of ~40 ms (complexity-invariant), enabling high-agility, collision-free navigation across diverse real-world cluttered environments. Default parameters exhibit strong generalization, ensuring robust system operation without scene-specific tuning.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Despite the growing impact of Unmanned Aerial Vehicles (UAVs) across various industries, most of current available solutions lack for 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 scenarios in which a safe and high maneuverability is required, due to the cluttered environment and the narrow rooms to move. The system combines an RRT* global planner with a newly proposed reactive planner, DWA-3D, which is the 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, easing 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 around 40 ms, regardless of the scenario complexity.

Problem

• Develop robust autonomous UAV navigation in confined spaces
• Optimize path planning parameters for safe obstacle avoidance
• Enable real-time 3D mapping without prior environment knowledge

Innovation

• Combines RRT* global planner with DWA-3D reactive planner
• Uses onboard LiDAR and Octomap for real-time 3D mapping
• Optimizes parameters for horizontal or vertical path prioritization