Micro Aerial Vehicles (MAVs) can be used for aerial transportation in remote and urban spaces where portability can be exploited to reach previously inaccessible and inhospitable spaces. Current approaches for path planning of MAV swung payload system either compute conservative minimal-swing trajectories or pre-generate agile collision-free trajectories. However, these approaches have failed to address the prospect of online re-planning in uncertain and dynamic environments, which is a prerequisite for real-world deployability. This paper describes an online method for agile and closed-loop local trajectory planning and control that relies on Non-Linear Model Predictive Control and that addresses the mentioned limitations of contemporary approaches. We integrate the controller in a full system framework, and demonstrate the algorithm’s effectiveness in simulation and in experimental studies. Results show the scalability and adaptability of our method to various dynamic setups with repeatable performance over several complex tasks that include flying through a narrow opening and avoiding moving humans.

中文翻译：

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动态环境中MAV有效载荷系统的在线轨迹规划和控制

微型飞行器（MAV）可用于偏远和城市空间的空中运输，在这些空间中，可利用其便携性到达以前人迹罕至且不适合居住的空间。MAV摆动有效载荷系统的路径规划的当前方法是计算保守的最小摆动轨迹或预先生成敏捷的无碰撞轨迹。但是，这些方法未能解决在不确定和动态环境中进行联机重新计划的前景，而这是现实世界中可部署性的前提。本文描述了一种基于非线性模型预测控制的敏捷和闭环局部轨迹规划和控制的在线方法，该方法解决了现代方法的上述局限性。我们将控制器整合到完整的系统框架中，并证明了该算法在仿真和实验研究中的有效性。结果显示了我们的方法对各种动态设置的可扩展性和适应性，在几个复杂的任务上具有可重复的性能，这些任务包括通过狭窄的开口飞行并避免移动人员。