eternpoler/tactile_teleoperation_dataset
Tactile Teleoperation Fruit Grasping Dataset Dataset of magnetometer (MAG) streams recorded during teleoperated robotic grasping of soft fruits, collected to study tactile signatures of grasp damage. Data Collection A robotic gripper was teleoperated to grasp fruits. Two IMU/magnetometer sensors mounted on the two sides of the gripper jaws recorded 3-axis data. Each recorded trial is stored as one CSV file. Labels (8 classes) Fruit type × grasp… See the full description on the dataset page: https://huggingface.co/datasets/eternpoler/tactile_teleoperation_dataset.
Tactile Teleoperation Fruit Grasping Dataset
Dataset of magnetometer (MAG) streams recorded during teleoperated robotic grasping of soft fruits, collected to study tactile signatures of grasp damage.
Data Collection
A robotic gripper was teleoperated to grasp fruits. Two IMU/magnetometer sensors mounted on the two sides of the gripper jaws recorded 3-axis data. Each recorded trial is stored as one CSV file.
Labels (8 classes)
Fruit type × grasp outcome (intact / damaged):
10 trials per class, 80 CSV files in total. The *_allplot folders contain per-trial waveform plots (PNG) for visualization / quality checking (60 PNG files).
CSV Format
Each CSV has the header:
timestamp,sensor_index,data_type,data_type_name,raw_x,raw_y,raw_z,si_x,si_y,si_ztimestamp— UNIX timestamp (seconds)sensor_index— sensor id (0 or 1, the two sensors on the two gripper jaws)data_type/data_type_name— sensor data type; use rows wheredata_type_name == "MAG"(magnetometer)raw_x, raw_y, raw_z— raw ADC valuessi_x, si_y, si_z— values in SI units (µT)
Each sensor provides a 3-channel (si_x, si_y, si_z) time series per trial.
Suggested Usage
- Time-series classification of grasp outcome (intact vs. damaged) per fruit type
- 8-class classification across fruit types and outcomes
- Cross-sensor fusion of the dual (sensor_index 0/1) streams
