Minimum-Time Sequential Traversal by a Team of Small Unmanned Aerial Vehicles in an Unknown Environment with Winds

TL;DR

This paper presents a method for a team of small UAVs to efficiently deliver packages in windy environments by sequentially estimating wind conditions and planning minimum-time paths, minimizing total travel time.

Contribution

It introduces a novel sequential traversal strategy for UAVs to estimate wind fields and optimize paths in unknown, dynamic environments, reducing total delivery time.

Findings

The method effectively estimates wind speeds during UAV flights.

UAVs find near-optimal paths with minimal traversals.

The approach adapts to static and dynamic wind conditions.

Abstract

We consider the problem of transporting multiple packages from an initial location to a destination location in a windy urban environment using a team of SUAVs. Each SUAV carries one package. We assume that the wind field is unknown, but wind speed can be measured by SUAVs during flight. The SUAVs fly sequentially one after the other, measure wind speeds along their trajectories, and report the measurements to a central computer. The overall objective is to minimize the total travel time of all SUAVs, which is in turn related to the number of SUAV traversals through the environment. For a discretized environment modeled by a graph, we describe a method to estimate wind speeds and the time of traversal for each SUAV path. Each SUAV traverses a minimum-time path planned based on the current wind field estimate. We study cases of static and time-varying wind fields with and without measurement noise. For each case, we demonstrate via numerical simulation that the proposed method finds the optimal path after a minimal number of traversals.