Towards Time-Optimal Tunnel-Following for Quadrotors
This addresses the challenge of agile quadrotor navigation in constrained settings, offering a trade-off between speed and safety, though it appears incremental by building on existing nonlinear model predictive control techniques.
The paper tackled the problem of real-time, time-optimal navigation for quadrotors in dynamic environments by developing a control method that approximates time-optimal behavior while staying within moving corridors, achieving simulated results capable of aggressive maneuvers, stop-and-go, and backward motions.
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.