Towards Time-Optimal Tunnel-Following for Quadrotors

TL;DR

This paper introduces a real-time control method for quadrotors that approximates time-optimal navigation within dynamic environments, enabling aggressive maneuvers while respecting changing spatial constraints.

Contribution

It presents a novel nonlinear model predictive control approach that handles dynamic corridors, improving upon static or offline methods for time-optimal quadrotor navigation.

Findings

Capable of aggressive maneuvers and stop-and-go motions

Maintains constraints within dynamic corridors

Demonstrates effectiveness in simulated environments

Abstract

Minimum-time navigation within constrained and dynamic environments is of special relevance in robotics. Seeking time-optimality, while guaranteeing the integrity of time-varying spatial bounds, is an appealing trade-off for agile vehicles, such as quadrotors. State of the art approaches, either assume bounds to be static and generate time-optimal trajectories offline, or compromise time-optimality for constraint satisfaction. Leveraging nonlinear model predictive control and a path parametric reformulation of the quadrotor model, we present a real-time control that approximates time-optimal behavior and remains within dynamic corridors. The efficacy of the approach is evaluated according to simulated results, showing itself capable of performing extremely aggressive maneuvers as well as stop-and-go and backward motions.