Tensegrity SuperBall Parameter Dataset

该数据集包含了20,000个训练数据点和2,000个测试数据点，这些数据是通过模拟器生成的，旨在识别基于不同采样参数的Tensegrity SuperBall机器人模型的参数。此外，该数据集从15维参数空间中生成，其采样值在真实值的±10%范围内，这有助于为Tensegrity机器人进行优化和控制实验。该数据集的规模为20,000个训练点和2,000个测试点，其任务是进行张拉整体运动模型的识别。

This dataset consists of 20,000 training data points and 2,000 test data points, all generated via a simulator, with the goal of identifying the parameters of the Tensegrity SuperBall robot model using different sampling parameters. Furthermore, this dataset is derived from a 15-dimensional parameter space, where all sampled values lie within ±10% of their ground-truth values, which supports optimization and control experiments for tensegrity robots. Featuring a total of 20,000 training samples and 2,000 test samples, the primary task of this dataset is to identify the kinematic model of tensegrity structures.