The role of a motion planner is pivotal in quadrotor applications, yet existing methods often struggle to adapt to complex environments, limiting their ability to achieve fast, safe, and robust flight. In this letter, we introduce a performance-enhanced quadrotor motion planner designed for autonomous flight in complex environments including dense obstacles, dynamic obstacles, and unknown disturbances. The global planner generates an initial trajectory through kinodynamic path searching and refines it using B-spline trajectory optimization. Subsequently, the local planner takes into account the quadrotor dynamics, estimated disturbance, global reference trajectory, control cost, time cost, and safety constraints to generate real-time control inputs, utilizing the framework of model predictive contouring control. Both simulations and real-world experiments corroborate the heightened robustness, safety, and speed of the proposed motion planner. Additionally, our motion planner achieves flights at more than 6.8 m/s in a challenging and complex racing scenario.

翻译：运动规划器在四旋翼应用中起着关键作用，但现有方法往往难以适应复杂环境，限制了其实现快速、安全、鲁棒飞行的能力。本文提出一种性能增强型四旋翼运动规划器，专为涵盖密集障碍物、动态障碍物及未知干扰的复杂环境中的自主飞行设计。全局规划器通过动力学路径搜索生成初始轨迹，并利用B样条轨迹优化进行精化。随后，局部规划器基于模型预测轮廓控制框架，综合考虑四旋翼动力学、估计干扰、全局参考轨迹、控制代价、时间代价及安全约束，生成实时控制输入。仿真与真实世界实验均验证了所提运动规划器在鲁棒性、安全性和速度方面的提升。此外，在挑战性复杂的竞速场景中，我们的运动规划器实现了超过6.8 m/s的飞行速度。