Dataset for magnetic soft robots and materials

(1) Dataset for magnetic soft robots and materials This dataset is a result of the "Data-driven design of shape-programmable magnetic soft materials" paper. Karacakol, A.C., Alapan, Y., Demir, S.O., Sitti M. Data-driven design of shape-programmable magnetic soft materials. Nat Commun 16, 2946 (2025). https://doi.org/10.1038/s41467-025-58091-z It involves a raw dataset of 53 learning runs (resulting in ~1.5e7 simulation evaluations) conducted for the demonstrations and algorithm benchmarking cases. Each data provides the position information of the robot in cartesian coordinates along its body at the final steady-state shape for a given design and actuation signal. The dataset is shared to enable further research in stimuli-responsive soft robotics and soft materials fields. (2) Github link for the project Public code repository for the "Data-driven design of shape-programmable magnetic soft materials" paper could be found in; https://github.com/AlpKaracakol/data_driven_magnetic_soft_material_design(1) 磁软机器人与材料数据集 本数据集源自论文《形状可编程磁软材料的数据驱动设计（Data-driven design of shape-programmable magnetic soft materials）》。 该论文作者为Karacakol, A.C.、Alapan, Y.、Demir, S.O.与Sitti M.，发表于《自然-通讯（Nature Communications）》16卷，第2946页（2025年），DOI为：https://doi.org/10.1038/s41467-025-58091-z。 本数据集包含用于演示实验与算法基准测试的53次学习运行的原始数据，共计约1.5×10^7次仿真评估。每条数据均提供了给定设计方案与驱动信号下，机器人本体在最终稳态形状下的笛卡尔坐标系位置信息。本数据集已公开共享，以推动刺激响应型软体机器人与软体材料领域的后续研究。 (2) 项目GitHub链接 本论文对应的公开代码仓库可通过以下地址获取： https://github.com/AlpKaracakol/data_driven_magnetic_soft_material_design