PhysicalAI-Robotics-mindmap-Checkpoints / model_explainability.md
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# 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](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/)