In this paper, we suggest an approach towards integrating planning with sequence models based on the idea of iterative energy minimization, and illustrate how such a procedure leads to improved RL performance across different tasks.
The OOD score is then determined by combining the deviation from the input data to the ID pattern in both subspaces.
We propose a new 6-DoF grasp pose synthesis approach from 2D/2. 5D input based on keypoints.
Great success has been achieved in the 6-DoF grasp learning from the point cloud input, yet the computational cost due to the point set orderlessness remains a concern.