Real-Time Quadrotor Trajectory Optimization with Time-Triggered Corridor Constraints

TL;DR

This paper presents a fast, real-time trajectory optimization method for quadrotors that approximates nonconvex corridor constraints with convex ones, enabling efficient collision-free flight in complex environments.

Contribution

A novel numerical approach combining bisection search and infeasibility detection to approximate nonconvex corridor constraints with convex constraints for real-time quadrotor trajectory optimization.

Findings

50-200 times faster than mixed integer programming

Effective in simulation and indoor flight with obstacles

Demonstrates real-time applicability for collision avoidance

Abstract

One of the keys to flying quadrotors is to optimize their trajectories within the set of collision-free corridors. These corridors impose nonconvex constraints on the trajectories, making real-time trajectory optimization challenging. We introduce a novel numerical method that approximates the nonconvex corridor constraints with time-triggered convex corridor constraints. This method combines bisection search and repeated infeasibility detection. We further develop a customized C++ implementation of the proposed method, based on a first-order conic optimization method that detects infeasibility and exploits problem structure. We demonstrate the efficiency and effectiveness of the proposed method using numerical simulation on randomly generated problem instances as well as indoor flight experiments with hoop obstacles. Compared with mixed integer programming, the proposed method is about 50--200 times faster.