Deformable Object Manipulation

• For each BDLO, dynamic trajectory data is captured in real-world settings using a motion capture system operating at 100 Hz when robots grasp the BDLO’s ends. For details on dataset usage, please refer to DEFT_train.py. - For BDLO 1 and BDLO 3, we record dynamic trajectory data when one robot grasps the middle of the BDLO while the other robot grasps one of its ends.

For each DLO, we collect 350 seconds of dynamic trajectory data in the real-world using the motion capture system at a frequency of 100 Hz.

Two versions of the dataset are offered: one is the full dataset used to train the models in DeformPAM, and the other is a mini dataset for easier examination. Both datasets include data for the supervised and finetuning stages of granular pile shaping, rope shaping, and T-shirt unfolding.

From https://github.com/MMintLab/VIRDO/blob/master/data/dataset_readme.txt, 1. DESCRIPTION: This dataset is written in 'dtype=torch.float64'. This dataset consists of total 144 deformation scenes from 6 different objects generated through MATLAB. It is divided into 'train' and 'test' dataset, where data['train'][OBJECT IDX = i][DEFORM IDX = j ] and data['test'][OBJECT IDX = i][DEFORM IDX = j ] indicates the same scene, but they are two different subsets of query points. 2. STRUCTURE: The dataset structure is as follows: VIRDO_simul_dataset = { 'train':{ <OBJECT IDX>: { 'nominal': { 'coords': tensor([1, M, 3]), 'normals': tensor([1, M, 3]), 'gt': tensor([1, M, 3]), 'scale': float }, <DEFORM IDX>: { 'coords': tensor([1, M, 3]), 'contact': tensor([1, M_c, 3]), 'normals': tensor([1, M, 3]), 'gt': tensor([1, M, 3]), 'scale': float, 'reaction': tensor([1,3] }, }, }, 'test':{ <OBJECT IDX>: { 'nominal': { 'coords': tensor([1, M, 3]), 'normals': tensor([1, M, 3]), 'gt': tensor([1, M, 3]), 'scale': float }, <DEFORM IDX>: { 'coords': tensor([1, M, 3]), 'contact': tensor([1, M_c, 3]), 'normals': tensor([1, M, 3]), 'gt': tensor([1, M, 3]), 'scale': float, 'reaction': tensor([1,3] }, }, }, } * <OBJECT IDX> = Interger from 0 ~ 5. Each number indicates different object. * <DEFORM IDX> = Unique integer for each deformation. * M = total points (on-surface + off-surface) * M_c = a subset of on-surface points that are in contact * [:,i,:] elements of 'coords', 'normals', and 'gt' refers ith query point of a scene. To get on-surface points of data_def = data['train'][<OBJECT IDX>][<DEFORM IDX>], you should do data_def['coords'][:,torch.where(data_def['gt'] == 0)[1],:].