基于扰动观测的安全控制，让无人机在不确定环境中更安全地完成物理交互。
Safety-Critical Control for Aerial Physical Interaction in Uncertain Environment
- 设计安全滤波器动态调整飞行姿态轨迹，融合扰动观测与推力限制。
- 理论证明即使估计有误差，也能保证推力在安全范围内。
- 实测在推墙、拔插头等任务中表现更优，尤其适合动态变化场景。
空中操作在机器人研究中日益受到关注，尤其在与环境进行安全物理交互方面。本文针对全驱动无人机机械臂，在静态与动态结构环境中，提出一种基于扰动观测器的安全关键控制方法。该方法的核心是一个安全滤波器，可动态调整飞行器姿态的期望轨迹，综合考虑无人机机械臂的动力学特性、扰动观测器结构及电机推力上限。我们严格证明了所提安全滤波器能确保安全集（即推力限制）的前向不变性，即使存在扰动估计误差。为验证方法优势，我们在复杂任务中进行了对比实验，包括推静止结构和牢固拔出插座中的插头。此外，为凸显其在突发动态变化下的重复性表现，还进行了多次推移动小车和拔插头测试。实验结果表明，该方法不仅优于现有策略，且在快速动态变化任务中表现出更强鲁棒性。
原文摘要 · Abstract (English)
Aerial manipulation for safe physical interaction with their environments is gaining significant momentum in robotics research. In this paper, we present a disturbance-observer-based safety-critical control for a fully actuated aerial manipulator interacting with both static and dynamic structures. Our approach centers on a safety filter that dynamically adjusts the desired trajectory of the vehicle's pose, accounting for the aerial manipulator's dynamics, the disturbance observer's structure, and motor thrust limits. We provide rigorous proof that the proposed safety filter ensures the forward invariance of the safety set - representing motor thrust limits - even in the presence of disturbance estimation errors. To demonstrate the superiority of our method over existing control strategies for aerial physical interaction, we perform comparative experiments involving complex tasks, such as pushing against a static structure and pulling a plug firmly attached to an electric socket. Furthermore, to highlight its repeatability in scenarios with sudden dynamic changes, we perform repeated tests of pushing a movable cart and extracting a plug from a socket. These experiments confirm that our method not only outperforms existing methods but also excels in handling tasks with rapid dynamic variations.
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