RoboLight: 一个具有线性可组合照明的机器人操作数据集
RoboLight: A Dataset with Linearly Composable Illumination for Robotic Manipulation
AI总结：
RoboLight数据集通过线性可组合照明技术，为机器人操作提供真实世界和合成数据，支持感知挑战和任务多样性研究。
摘要：
在本文中，我们介绍了RoboLight，第一个真实世界机器人操作数据集，该数据集在系统性变化的光照条件下捕捉同步事件。RoboLight由两个组成部分组成。(a) RoboLight-Real包含2,800个在我们定制的Light Cube设置中收集的真实世界事件，这是一个校准系统，配备八个可编程的RGB LED灯。它包括沿三个独立控制维度的结构化照明变化：颜色、方向和强度。每个维度都配对一个专门的任务，包含几何形状和材料各异的物体以引发感知挑战。所有图像数据都以高动态范围（HDR）格式记录，以保持辐射计量准确性。利用光传输的线性性，我们引入了(b) RoboLight-Synthetic，通过在RoboLight-Real的HDR图像空间中进行插值合成196,000个事件。原则上，RoboLight-Synthetic可以通过细化插值粒度任意扩展。我们还通过定性分析和现实世界策略滚动验证数据集质量，分析任务难度、分布多样性以及合成数据的有效性。我们还展示了所提数据集的三个代表性应用案例。完整的数据集，以及系统软件和硬件设计，将作为开源发布，以支持持续研究。
英文摘要：
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.
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