Tactile-Based Robotic Peg Extraction Dataset

This dataset provides robotic and tactile sensor data captured using two multi-modal tactile sensing (BioIn-Tacto [1, 2]) modules mounted on the end-effector of an OpenManipulator X. The sensor includes barometric and MARG (Magnetic, Angular Rate, and Gravity) data to support research in tactile manipulation. The dataset was collected in teleoperation experiments involving the extraction of differently shaped pegs from a base with holes using a robotic manipulator arm. The total number of extraction episodes in the dataset is 96. The dataset also includes Reinforcement Learning pre-trained data. The dataset can be used to pre-train a reinforcement learning model to perform peg-in-hole tasks and to study how pre-training affects a manipulator’s ability to infer tactile signals and improve success rates of the manipulator.

The data is organized into folders representing each object runs:

Data/
└RL/
│ └Object<1|2|3|>
│ └recordstep__object<1|2|3>_pretained_.csv
└Teleop/
├csv2dataframe.py
├README.md
└──csv/
└Object<1|2|3|>/
└robot_O<1|2|3>_T_A<0|45|90|135|180>_/
├imu1_data_raw.csv
├imu1_mag.csv
├imu2_data_raw.csv
├imu2_mag.csv
├imu_data1.csv
├imu_data2.csv
├joint_states.csv
├m_baros_serial1.csv
├m_baros_serial2.csv
├pressure_viz_left.csv
├pressure_viz_right.csv
├raw_barometers_teensy1.csv
├raw_barometers_teensy2.csv
├raw_imu_teensy1.csv
├raw_imu_teensy2.csv
├robot_instruction.csv
├tf.csv
└tf_static.csv

- csv2dataframe.py: Converts the data into dataframes
- Object<1|2|3|>/: Three folders with data from each object
- recordstep__object<1|2|3>_pretained_: Files with RL data for each object.
- robot_O<1|2|3>_T_A<0|45|90|135|180>_/: Data dollected from each object at different angles.

[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.