Ex-DoF: Expansion of Action Degree-of-Freedom with Virtual Camera Rotation for Omnidirectional Image
This addresses data transfer challenges in robot control for manipulation tasks, but it is incremental as it builds on existing transfer learning and data augmentation methods.
The paper tackles the problem of transferring training data from a lower-DoF robot to a higher-DoF one using omnidirectional camera images, with virtual camera rotation for data augmentation, and demonstrates training a 6-DoF robot control policy from a 3-DoF dataset and applying it to object reaching tasks.
Inter-robot transfer of training data is a little explored topic in learning- and vision-based robot control. Here we propose a transfer method from a robot with a lower Degree-of-Freedom (DoF) to one with a higher DoF utilizing the omnidirectional camera image. The virtual rotation of the robot camera enables data augmentation in this transfer learning process. As an experimental demonstration, a vision-based control policy for a 6-DoF robot is trained using a dataset collected by a wheeled ground robot with only three DoFs. Towards the application of robotic manipulations, we also demonstrate a control system of a 6-DoF arm robot using multiple policies with different fields of view to enable object reaching tasks.