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Synthetic Multimodal Dataset using ABB Studio: Single Robot Welding Station

<p>## README</p> <p>### Overview</p> <p>This repository provides the setup and data collected from simulations conducted in RobotStudio for various ABB robot configurations. The simulation, based on L&ouml;ppenberg et al. (2024), was designed to capture precise sensory data in a controlled environment that mirrors real-world welding conditions.</p> <p>### Simulation Setup</p> <p>The simulation tracks essential parameters of the ABB robot and its end-effector, including:<br>- **Joint Angles**: Real-time angles for each joint.<br>- **TCP Position**: 3D positional coordinates of the Tool Center Point.<br>- **TCP Orientation**: Orientation captured as quaternions to represent rotational states.<br>- **Additional Attributes**: Various other robot-specific details relevant to performance in a welding setup.</p> <p>### Data Collection</p> <p>To generate a high-resolution dataset, data were sampled at intervals between 12 ms and 96 ms. This detailed sampling provides accurate insights into the robot's operation in a simulated welding environment.</p> <p>### Key Parameters</p> <p>The dataset includes the following parameters:</p> <p>- **Camera View**: One camera view with a resolution of 3 x 256 x 256, normalized to the range [0, 1].<br>- **Motor Power (P)**: The power consumed by the robot&rsquo;s motors, constrained within \([0, P_{\text{max}}]\).<br>- **TCP Speed (v_TCP)**: The velocity of the end-effector, with a maximum cap of 5 m/s.<br>- **TCP Acceleration (a_TCP)**: The acceleration of the TCP, bounded within \([a_{\text{min}}, a_{\text{max}}]\).<br>- **TCP Orientation (q_TCP)**: Quaternion representing orientation, with a normalization condition \(||\mathbf{q}_{\text{TCP}}(t)|| = 1\).<br>- **TCP Position (p_TCP)**: A 3D vector for positional coordinates, with each coordinate constrained within \([p_{\text{min}}, p_{\text{max}}]\).<br>- **Braking Distance (d_brake)**: The distance each joint travels during braking, within bounds \([d_{\text{min}}, d_{\text{max}}]\).<br>- **Holding Position (&theta;_hold)**: The maintained angles for each joint, constrained to the interval \([-&pi;, &pi;]\).<br>- **Joint Angles (&theta;)**: The current angles of each joint, also within the interval \([-&pi;, &pi;]\).</p> <p>Frame '02655_frame' is corrupted. That means the corresponding values of the other modality needs to be removed as well.</p> <p><br>### Citation</p> <p>For more details on the simulation methodology, please refer to:<br>- L&ouml;ppenberg, M., Yuwono, S., Diprasetya, M. R., &amp; Schwung, A. (2024). Dynamic robot routing optimization: State-space decomposition for operations research-informed reinforcement learning. Robotics and Computer-Integrated Manufacturing, 90, 102812.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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