model_explainability.md

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