Dense Fixed-Wing Swarming using Receding-Horizon NMPC

TL;DR

This paper introduces a receding-horizon NMPC method for controlling fixed-wing drone swarms in close proximity, ensuring collision avoidance and enabling physical aerobatic swarming, validated through simulations and hardware tests.

Contribution

It presents a novel NMPC-based control approach for fixed-wing swarms that handles close-quarters maneuvering and collision avoidance, with a new probabilistic safety metric.

Findings

Successful demonstration of close-quarters fixed-wing swarming in hardware

Development of a statistical bound for collision probability

First physical implementation of fixed-wing aerobatic swarm

Abstract

In this paper, we present an approach for controlling a team of agile fixed-wing aerial vehicles in close proximity to one another. Our approach relies on receding-horizon nonlinear model predictive control (NMPC) to plan maneuvers across an expanded flight envelope to enable inter-agent collision avoidance. To facilitate robust collision avoidance and characterize the likelihood of inter-agent collisions, we compute a statistical bound on the probability of the system leaving a tube around the planned nominal trajectory. Finally, we propose a metric for evaluating highly dynamic swarms and use this metric to evaluate our approach. We successfully demonstrated our approach through both simulation and hardware experiments, and to our knowledge, this the first time close-quarters swarming has been achieved with physical aerobatic fixed-wing vehicles.