外观
论文arXiv 2608.140492 个月前
FlatLab：用于扁平物体机器人操作的统一方法框架与基于仿真的基准
原文链接：FlatLab: A Unified Methodology Framework and Simulation-Based Benchmark for Robotic Manipulation of Flat Objects（arXiv 2608.14049 · 发布日期：2026-08-14）
FlatLab: A Unified Methodology Framework and Simulation-Based Benchmark for Robotic Manipulation of Flat Objects
面向扁平物体难抓取与泛化问题，提出策略生成与动作执行解耦框架，并在FlatLab仿真基准验证。
核心要点
- 扁平物体存在不可抓取构型，几何与材料变化大，现有方法依赖启发式预操作且泛化受限。
- 框架将操作解耦为策略生成器和动作执行模块，从点云预测策略并组合可复用动作基元生成轨迹。
- FlatLab提供多样刚性与可变形扁平物体的高保真仿真、自动多模态采集和标准化评测协议。
- 在FlatLab中的实验显示，该方法可泛化到未见物体和类别，并优于现有基线；项目页和代码已提供。
验证范围与局限：验证范围为FlatLab仿真基准中的扁平物体操作任务。
英文摘要 (Abstract)
Robotic manipulation of flat objects is challenging due to the ungraspable configurations and strong variations in object geometry and material. Existing methods rely on heuristic pre-manipulation and are often evaluated in closed settings with limited generalization. We propose a unified framework that decouples the manipulation into a strategy generator and an action execution module. The strategy generator predicts appropriate manipulation strategies from object point clouds by learning strategy-centric, object-invariant representations via simulated data transformation and contrastive learning. Conditioned on the predicted strategy, the execution module decomposes long-horizon manipulation into reusable action primitives and dynamically composes them to generate stable trajectories. To enable systematic evaluation, we introduce FlatLab, a comprehensive simulation benchmark for robotic flat object manipulation. FlatLab provides high-fidelity physical simulation of diverse rigid and deformable flat objects, automated multi-modal data collection, and standardized task definitions and evaluation protocols. Experiments conducted in FlatLab demonstrate that our approach generalizes effectively to unseen objects and categories, outperforming existing baselines. The project page and the code are provided at https://flatlab-web.github.io/.
作者：Xingyu Zhu, Wenshuo Han, Zhouyu Wang, Yuran Wang, Ruihai Wu, Hao Dong, Fan Tang, Hechang Chen, Hyung Jin Chang, Yixing Gao
来源
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