Data of paper "A Grip Force Planning Method for Reliable and Rapid Fruit Grasping Based on Rupture Force Estimation"

In the related paper, we proposed an online estimation method of fruit rupture force based on stiffness perception. This dataset includes the training data and the online validation data, based on which we got and validated the relationship between the rupture forces and the stiffness of banana slices and kiwi slices. This dataset consists of two folders: banana and kiwi, standing for the data of bananas and kiwis, respectively. Each folder includes two sub folders training set and validation set. The training set includes the data for training the relationship between rupture force and stiffness. In this folder, the data are stored with an python script train_model.py, which is used to get the linear relation proposed in the paper. The validation set includes the the data for validation the online estimation performance. In this folder, the data are stored with an python script break_force_est_offline.py, which is to simulate the online estimation process and output the final estimation of rupture force based on the collected data. The data in the dataset are collected in the way mentioned in the paper.在相关研究论文中，我们提出了一种基于刚度感知的水果破裂力在线估计方法。本数据集包含训练数据与在线验证数据，依托该数据集我们得以推导并验证了香蕉切片与猕猴桃切片的破裂力与刚度之间的关联关系。 本数据集包含两个文件夹，分别为banana与kiwi，对应香蕉与猕猴桃的相关数据。每个文件夹下均设有两个子文件夹：训练集（training set）与验证集（validation set）。训练集文件夹用于存储推导破裂力与刚度关联关系的训练数据，该文件夹内附带Python脚本train_model.py，用于实现论文中提出的线性关联关系推导。验证集文件夹用于存储在线估计性能验证所需的数据，该文件夹内附带Python脚本break_force_est_offline.py，用于模拟在线估计流程，并基于采集到的数据输出最终的破裂力估计结果。 本数据集内的所有数据均按照论文中提及的方式进行采集。