Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance

TL;DR

This paper introduces a robust model predictive control approach for aircraft collision avoidance that effectively incorporates intent information and manages uncertainties in multi-agent horizontal maneuvers.

Contribution

It proposes a scenario tree MPC method that integrates aircraft intent and uncertainties, enhancing collision avoidance robustness and computational efficiency.

Findings

Successfully integrates intent information into collision avoidance.

Demonstrates robustness against uncertainties in simulations.

Offers computationally efficient control scheme.

Abstract

This paper presents the use of robust model predictive control for the design of an intent-aware collision avoidance system for multi-agent aircraft engaged in horizontal maneuvering scenarios. We assume that information from other agents is accessible in the form of waypoints or destinations. Consequently, we consider that other agents follow their optimal Dubin's path--a trajectory that connects their current state to their intended state--while accounting for potential uncertainties. We propose using scenario tree model predictive control as a robust approach that demonstrates computational efficiency. We demonstrate that the proposed method can easily integrate intent information and offer a robust scheme that handles different uncertainties. The method is illustrated through simulation results.