Dynamic Tactile Data of Textures On Uneven Surfaces

Description

This dataset provides tactile sensor data captured using an a multi-modal tactile sensing (BioIn-Tacto [1, 2]) module mounted on the end-effector of a OpenManipulatorX. It includes barometric and MARG (Magnetic, Angular Rate, and Gravity) data to support research in texture recognition and robotic manipulation. The data was collected as the manipulator moved the sensing module across 12 different textures applied to a concave/convex surface. The data is organized into folders representing various stages of processing: Data/ ├── 0_Raw ├── 1_Merged ├── 2_Trimmed ├── 3_Normalized └── 4_Windowed - 0_Raw: Raw data for 12 textures (T1 to T12), with 25 exploratory movements per texture. - 1_Merged: Merged barometric and IMU data. - 2_Trimmed: Preprocessed and trimmed data. - 3_Normalized: Normalized data for consistency. - 4_Windowed: Data segmented into windows for analysis. Each exploratory movement contains the following files: - `baro.csv`: Barometric data. - `imus.csv`: IMU data (acceleration, angular rate, and magnetic field). The `Scripts` folder includes tools for automating data preprocessing: Scripts/ ├── merge.py ├── trim.py ├── normalize.py ├── window_creator.py ├── npy_creator.py └── run.sh - merge.py: Merges barometric and IMU data. - trim.py: Trims data based on predefined points. - normalize.py: Normalizes data for consistency. - window_creator.py: Segments data into windows. - npy_creator.py: Converts CSV data into `.npy` format for machine learning. - run.sh: Automates the entire data preprocessing pipeline. It sequentially runs the following steps: 1. Merges barometric and IMU data from the raw data directory (`merge.py`). 2. Trims the merged data based on predefined points stored in `trim_points.json` (`trim.py`). 3. Normalizes the trimmed data for consistency (`normalize.py`). 4. Segments the normalized data into windows of varying sizes (`window_creator.py`). 5. Converts the windowed data into `.npy` format for machine learning models with window sizes of 128, 256, and 512 (`npy_creator.py`). [1] T. E. Alves de Oliveira, A. -M. Cretu and E. M. Petriu, "Multimodal Bio-Inspired Tactile Sensing Module," in IEEE Sensors Journal, vol. 17, no. 11, pp. 3231-3243, 1 June1, 2017, https://doi.org/10.1109/JSEN.2017.2690898. [2] T. E. Alves de Oliveira, V. Prado da Fonseca, BioIn-Tacto: A compliant multi-modal tactile sensing module for robotic tasks, HardwareX, Volume 16, 2023, e00478, ISSN 2468-0672, https://doi.org/10.1016/j.ohx.2023.e00478.

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