Constraint-Aware Trajectory for Drone Delivery Services

TL;DR

This paper demonstrates a drone delivery system within a skyway network, analyzing how different flight patterns and environmental factors affect drone performance through experimental data collection.

Contribution

It introduces a constraint-aware trajectory planning approach for drone delivery, validated through extensive experiments with Crazyflie drones.

Findings

Flight patterns impact battery consumption and stability.

Wind conditions significantly affect drone trajectories.

Experimental data supports trajectory optimization strategies.

Abstract

Drones are becoming a novel means for delivery services. We present a demonstration of drone delivery services in a skyway network that uses the service paradigm. A set of experiments is conducted using Crazyflie drones to collect the data on various positions of drones, wind speed, wind direction, and battery consumption. We run the experiments for a range of flight patterns including linear, rectangular, and triangular shapes.