Distracting Control Suite

Distracting Control Suite是由谷歌机器人研究团队开发的一个挑战性基准数据集，旨在为基于视觉的控制提供更接近真实世界视觉复杂性的模拟环境。该数据集扩展自DeepMind Control Suite，引入了三种视觉干扰类型：随机颜色变化、随机视频背景和随机相机姿态变化，以模拟真实世界中的视觉干扰。数据集包含6个任务，每个任务的难度可从几乎不可察觉调整到极其干扰。这些干扰可以在静态设置中仅在情节转换时改变，或在动态设置中平滑地在帧之间变化。Distracting Control Suite旨在通过提供一个统一且具有挑战性的基准，推动基于像素的强化学习方法的发展，特别是在处理真实世界视觉复杂性方面。

The Distracting Control Suite is a challenging benchmark dataset developed by the Google Robotics Research team, which aims to provide simulated environments that approximate real-world visual complexity for vision-based control tasks. Derived from the DeepMind Control Suite, this dataset introduces three types of visual distractions: random color variations, random video backgrounds, and random camera pose changes, to simulate the visual disturbances encountered in real-world scenarios. The dataset includes 6 tasks, with each task's difficulty adjustable from barely perceptible to highly distracting. These distractions can be modified only during episode transitions in static settings, or smoothly transition between consecutive frames in dynamic settings. The Distracting Control Suite aims to advance the development of pixel-based reinforcement learning methods, particularly in addressing real-world visual complexity, by providing a unified and challenging benchmark.