为四旋翼无人机规划安全轨迹，实时保障飞行稳定与避障。
Safety Assurance for Quadrotor Kinodynamic Motion Planning
- 用采样法生成无碰撞路径，再通过安全滤波器约束控制输入。
- 在Crazyflie 2.0仿真中实现3D环境下的轨迹跟踪与安全保证。
- 适合需要高可靠性的无人机自主导航场景，如搜救与巡检。
自主无人机在搜救、巡检和配送等真实场景中受到广泛关注。随着其在民用领域的普及，运行不安全可能导致系统损坏、环境污染甚至人员伤亡。尽管现有运动规划方法能生成无碰撞轨迹，但未考虑系统的安全操作区域，部署时仍可能违反安全约束。本文提出一种基于运行时安全保证的运动规划方法，在四旋翼无人机的运动规划中确保系统操作约束。首先，采用基于采样的几何规划器在用户定义空间内生成高层无碰撞路径；其次，设计低层安全保证滤波器，对线性二次调节器（LQR）的控制输入进行约束，以保障轨迹跟踪过程中的安全性。我们在限制的3D仿真环境中，使用Crazyflie 2.0无人机模型验证了该方法的有效性。
原文摘要 · Abstract (English)
Autonomous drones have gained considerable attention for applications in real-world scenarios, such as search and rescue, inspection, and delivery. As their use becomes ever more pervasive in civilian applications, failure to ensure safe operation can lead to physical damage to the system, environmental pollution, and even loss of human life. Recent work has demonstrated that motion planning techniques effectively generate a collision-free trajectory during navigation. However, these methods, while creating the motion plans, do not inherently consider the safe operational region of the system, leading to potential safety constraints violation during deployment. In this paper, we propose a method that leverages run time safety assurance in a kinodynamic motion planning scheme to satisfy the system's operational constraints. First, we use a sampling-based geometric planner to determine a high-level collision-free path within a user-defined space. Second, we design a low-level safety assurance filter to provide safety guarantees to the control input of a Linear Quadratic Regulator (LQR) designed with the purpose of trajectory tracking. We demonstrate our proposed approach in a restricted 3D simulation environment using a model of the Crazyflie 2.0 drone.
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