Achieving multi uav best viewpoint coordination in obstructed environments

TL;DR

This paper presents a hierarchical control system for multi-UAV wildfire suppression, integrating a novel line-of-sight obstacle avoidance method and path integral control to optimize viewpoints and trajectories, validated through simulations.

Contribution

It introduces a new control architecture combining obstacle avoidance and trajectory optimization for multi-UAV wildfire suppression in obstructed environments.

Findings

44.0% increase in effectiveness with line-of-sight obstacle avoidance

up to 39.6% improvement with path integral control

significant performance gains demonstrated in simulation studies

Abstract

Wildfire suppression is a complex task that poses high risks to humans. Using robotic teams for wildfire suppression enhances the safety and efficiency of detecting, monitoring, and extinguishing fires. We propose a control architecture based on task hierarchical control for the autonomous steering of a system of flying robots in wildfire suppression. We incorporate a novel line-of-sight obstacle avoidance method that calculates the best viewpoints and ensures an occlusion-free view for the suppression robot during the mission. Path integral control generates optimal trajectories towards the goals. We conduct an ablation study to assess the effectiveness of our approach by comparing it to scenarios where these key components are excluded, in order to validate the approach in simulations using Matlab and Unity. The results demonstrate significant performance improvements, with 44.0 % increase in effectiveness with the new line-of-sight obstacle avoidance task and up to 39.6 % improvement when using path integral control.