Uncertainty has long been a critical area of study in robotics, particularly when robots are equipped with analytical models. As we move towards the widespread use of deep neural networks in robots, which have demonstrated remarkable performance in research settings, understanding the nuances of uncertainty becomes crucial for their real-world deployment. This guide offers an overview of the importance of uncertainty and provides methods to quantify and evaluate it from an applications perspective.

翻译：不确定性长期以来一直是机器人学中的关键研究领域，尤其是在机器人配备分析模型时。随着深度神经网络在机器人中的广泛应用——这些网络在研究环境中已展现出卓越性能——理解不确定性的细微差别对于其实世界部署至关重要。本指南概述了不确定性的重要性，并从应用视角提供了量化与评估其的方法。