Model Predictive Contouring Control for Time-Optimal Quadrotor Flight
Model Predictive Contouring Control for Time-Optimal Quadrotor Flight
复制标题
时间最优四旋翼飞行器模型预测轮廓控制
DOI：
10.1109/tro.2022.3173711
复制
发表时间：
2021
影响因子：
7.8
通讯作者：
D. Scaramuzza
中科院分区：
文献类型：
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作者：
Angel Romero;Sihao Sun;Philipp Foehn;D. Scaramuzza
在这篇文章中，我们解决了飞行时间最佳轨迹通过多个航路点与四旋翼的问题。最先进的解决方案将问题分解为规划任务（生成全局时间最优轨迹）和控制任务（精确跟踪该轨迹）。然而，在当前状态下，生成考虑全四旋翼模型的时间最优轨迹需要通过优化来解决困难的时间分配问题，这在计算上是苛刻的（大约几分钟或甚至几小时）。这不利于在发生骚乱时重新规划。我们通过模型预测轮廓控制（MPCC）同时解决时间分配问题和控制问题来克服这个问题。我们的MPCC最佳选择的未来状态的平台在运行时，同时最大限度地提高了沿着参考路径的进展，并尽量减少到它的距离。我们表明，即使在跟踪简化的轨迹，建议的MPCC结果在一个路径，接近真正的时间最优的，并可以在真实的时间生成。我们在真实的世界中验证了我们的方法，在那里我们表明，我们的方法在单圈时间方面优于当前最先进的技术和世界级的人类飞行员，速度高达60公里/小时。
In this article, we tackle the problem of flying time-optimal trajectories through multiple waypoints with quadrotors. State-of-the-art solutions split the problem into a planning task—where a global time-optimal trajectory is generated—and a control task—where this trajectory is accurately tracked. However, at the current state, generating a time-optimal trajectory that considers the full quadrotor model requires solving a difficult time allocation problem via optimization, which is computationally demanding (in the order of minutes or even hours). This is detrimental for replanning in the presence of disturbances. We overcome this issue by solving the time allocation problem and the control problem concurrently via Model Predictive Contouring Control (MPCC). Our MPCC optimally selects the future states of the platform at runtime, while maximizing the progress along the reference path and minimizing the distance to it. We show that, even when tracking simplified trajectories, the proposed MPCC results in a path that approaches the true time-optimal one, and which can be generated in real time. We validate our approach in the real world, where we show that our method outperforms both the current state of the art and a world-class human pilot in terms of lap time achieving speeds of up to 60 km/h.