Documenting sensor data and pose estimations from an Aubo i5 dual-arm collaborative robot and an Intel RealSense D435 camera. It focuses on 3D object pose estimation using the Deep Object Pose Estimation (DOPE) method within a ROS-compatible structure.
Use Cases
- Train 3D pose estimation models using the RealSense D435 RGB-D data streams
- Develop dual-arm coordination scripts for the Aubo i5 based on object pose coordinates
- Test ROS perception pipelines using the integrated DOPE pose estimation outputs
Strengths
- Features data from an Aubo i5 dual-arm collaborative robot setup
- Utilizes Intel RealSense D435 camera for visual and depth input
- Contains 3D object pose estimation data generated via the DOPE algorithm
- Formatted for use within the Robot Operating System (ROS) framework