Accurately estimating risk in real-time is essential for ensuring the safety and efficiency of many applications involving autonomous robot systems. This paper presents a novel, generalizable algorithm for the real-time estimation of risks created by external disturbances on multirotors. Unlike conventional approaches, our method requires no additional sensors, accurate drone models, or large datasets. It employs motor command data in a fuzzy logic system, overcoming barriers to real-world implementation. Inherently adaptable, it utilizes fundamental drone characteristics, making it applicable to diverse drone models. The efficiency of the algorithm has been confirmed through comprehensive real-world testing on various platforms. It proficiently discerned between high and low-risk scenarios resulting from diverse wind disturbances and varying thrust-to-weight ratios. The algorithm surpassed the widely-recognized ArduCopter wind estimation algorithm in performance and demonstrated its capability to promptly detect brief gusts.

翻译：实时准确估计风险对于确保自主机器人系统在众多应用中的安全性和效率至关重要。本文提出了一种新颖且具有可泛化性的算法，用于实时估计多旋翼飞行器受外部扰动所产生的风险。与传统方法不同，本方法无需额外传感器、精确的无人机模型或大规模数据集。该算法利用模糊逻辑系统中的电机控制指令数据，克服了实际部署中的障碍。其固有其适应能力，仅需利用无人机基本特性，即可适用于多种无人机型号。通过在不同平台上进行的全面实际测试，验证了该算法的有效性。它能精准区分由不同风力扰动和不同推力重量比所导致的高风险与低风险场景。该算法性能超越了广泛认可的ArduCopter风力估计算法，并展示了快速检测短时阵风的能力。