policy
isaacgym-anymal-training
sathwik58 · IsaacLab
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Overview
Name
isaacgym-anymal-training
Author
sathwik58
Framework
IsaacLab
License
unknown
Skill type
locomotion
Evidence level
untested
Task description
Training ANYmal-C quadruped robot to walk using Proximal Policy Optimization (PPO) in NVIDIA Isaac Gym physics simulator. Implements actor-critic neural networks for robust locomotion control across various terrains.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list isaacgym-anymal-training yet.
Datasets that reference this policy
0No datasets reference isaacgym-anymal-training yet.