Explainability
| Field | Response |
|---|---|
| Intended Task/Domain: | Robotic Manipulation |
| Model Type: | Denoising Diffusion Probabilistic Model |
| Intended Users: | Roboticists and researchers in academia and industry who are interested in robot manipulation research |
| Output: | Actions consisting of end-effector poses, gripper states and head orientation. |
| Describe how the model works: | mindmap is a Denoising Diffusion Probabilistic Model that samples robot trajectories conditioned on sensor observations and a 3D reconstruction of the environment. |
| Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable |
| Technical Limitations & Mitigation: | - Limitation: This policy is only effective in the exact simulation environment in which it was trained. Mitigation: Recommended to retrain the model in new simulation environments. - Limitation: The policy was not tested on a physical robot and likely only works in simulation. Mitigation: Expand training, testing and validation on physical robot platforms. |
| Verified to have met prescribed NVIDIA quality standards: | Yes |
| Performance Metrics: | Closed loop success rate on simulated robotic manipulation tasks. |
| Potential Known Risks: | The model might be susceptible to rendering changes on the simulation tasks it was trained on. |
| Licensing: | NVIDIA Open Model License Agreement |