In this paper, we introduce RoboLight, the first real-world robotic manipulation dataset capturing synchronized episodes under systematically varied lighting conditions. RoboLight consists of two components. (a) RoboLight-Real contains 2,800 real-world episodes collected in our custom Light Cube setup, a calibrated system equipped with eight programmable RGB LED lights. It includes structured illumination variation along three independently controlled dimensions: color, direction, and intensity. Each dimension is paired with a dedicated task featuring objects of diverse geometries and materials to induce perceptual challenges. All image data are recorded in high-dynamic-range (HDR) format to preserve radiometric accuracy. Leveraging the linearity of light transport, we introduce (b) RoboLight-Synthetic, comprising 196,000 episodes synthesized through interpolation in the HDR image space of RoboLight-Real. In principle, RoboLight-Synthetic can be arbitrarily expanded by refining the interpolation granularity. We further verify the dataset quality through qualitative analysis and real-world policy roll-outs, analyzing task difficulty, distributional diversity, and the effectiveness of synthesized data. We additionally demonstrate three representative use cases of the proposed dataset. The full dataset, along with the system software and hardware design, will be released as open-source to support continued research.

翻译：本文介绍了RoboLight，首个在系统变化光照条件下捕获同步操作序列的真实世界机器人操作数据集。RoboLight包含两个组成部分：(a) RoboLight-Real包含2,800个在定制化光立方装置中采集的真实世界操作序列，该装置是一个配备八个可编程RGB LED灯的标定系统。它包含沿三个独立控制维度（颜色、方向与强度）的结构化光照变化。每个维度均配有专门设计的任务，其中包含不同几何形状与材质的物体以引发感知挑战。所有图像数据均以高动态范围格式记录以保持辐射测量精度。利用光传输的线性特性，我们提出了(b) RoboLight-Synthetic，包含通过RoboLight-Real的HDR图像空间插值合成的196,000个操作序列。理论上，通过细化插值粒度可无限扩展RoboLight-Synthetic。我们进一步通过定性分析和真实世界策略部署验证了数据集质量，分析了任务难度、分布多样性及合成数据的有效性。此外，我们展示了该数据集的三个代表性应用场景。完整数据集及系统软硬件设计将作为开源项目发布，以支持持续研究。