Datasets for classification and regression in human-robot interaction with parallel robots

This repository contains three datasets for the analysis of contact events in robots. The data was recorded using a parallel robot and is suitable for regression and classification tasks in the field of machine learning.

The datasets are divided into the following three tasks:

1. Regression of Contact Location and Force: The goal is to predict the location and force of a contact on the robot.
2. Classification of the Collided Body: This task aims to identify the robot's body that is in contact with the environment (one of the six links or the end-effector platform).
3. Classification of the Contact Type: This task deals with distinguishing between different types of contact, such as collisions and clamping.

More details on the first two datasets can be found in the publication: https://doi.org/10.1109/IROS55552.2023.10342345

Information on the third dataset can be found here: https://doi.org/10.1109/IROS55552.2023.10341581

Data Description

The data is available in .csv format and contains time-series data from the robot's sensors and a force-torque sensor. More information on the datasets can be found in their readme-files. The following variables are included in the datasets:

• t_s: Time (s)
• q_des_deg_[1-9]: Target joint angle for joints 1-9 (deg)
• q_deg_[1-9]: Actual joint angle for joints 1-9 (deg)
• x_des_m_rad_[1-3]: Target end-effector pose (x, y, orientation) (m, deg)
• x_m_rad_[1-3]: Actual end-effector pose (x, y, orientation) (m, deg)
• xd_ms_rads_[1-3]: Actual end-effector velocity (x, y, orientation) (m/s, deg/s)
• tau_qa_Nm_[1-3]: Actual motor torque for motors 1-3 (Nm)
• tau_ext_fts_Nm_[1-3]: External torque projected from force-torque sensor (Nm)
• tau_ext_est_Nm_[1-3]: Estimated external torque (Nm)
• F_ext_fts_N_Nm_[1-6]: External forces (1-3) and moments (4-6) from force-torque sensor (N, Nm)
• F_ext_est_mobPlat_CS0_N_Nm_[1-3]: Estimated external force and moment on the mobile end-effector platform (N, Nm)
• F_ext_fts_proj_mobPlat_CS0_N_Nm_[1-3]: Measured and projected external force and moment on the mobile end-effector platform (N, Nm)
• distances_m_[1-3]: Distances for classification (m)
• angles_deg_[1-3]: Angles for classification (deg)
• collided_body: Identifier for the body in contact (1-6=links, 7=platform) (-)
• chain: Collided chain (-)
• link: Collided link of the chain (-)
• location: Normalized location of the contact point on the link (-)
• clamping_collision: Identifier for the type of contact (0=collision, 1=clamping) (-)

Target Variables

• Regression: location and the third component of F_ext_fts_N_Nm_[1-6] (link-orthogonal force).
• Classification of the Collided Body: collided_body.
• Classification of the Contact Type: clamping_collision.

Usage

The datasets are available as train.csv and test.csv (for the classification tasks) and data.csv (for the regression task). They can be loaded using common libraries like Pandas in Python to train and evaluate machine learning models.

Citation

If you use these datasets in your research, please cite the corresponding publications.