---
tags:
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
- ppo
- pusher-v5
- mujoco
- robotics
library_name: stable-baselines3
---

# PPO Agent for Gymnasium MuJoCo `Pusher-v5`

This model is a high-performance **PPO** agent controlling a 7-DOF robotic arm to push a cylinder towards a target in Gymnasium **MuJoCo `Pusher-v5`**.

Trained and exported directly via **MuJoCo Pusher RL Studio Pro**.

## 🦾 Environment Details
- **Environment**: `Pusher-v5` (Gymnasium / MuJoCo)
- **Algorithm**: PPO (Stable-Baselines3)
- **Observation Space**: 23 dimensions (joint angles, velocities, tip, object, goal coordinates)
- **Action Space**: 7 dimensions (torque controls in range [-2.0, +2.0] Nm)

## 🚀 Usage (Stable-Baselines3)
```python
import gymnasium as gym
from stable_baselines3 import PPO

env = gym.make("Pusher-v5", render_mode="human")
model = PPO.load("ppo_pusher_latest.zip")

obs, _ = env.reset()
for _ in range(1000):
    action, _ = model.predict(obs, deterministic=True)
    obs, reward, done, truncated, _ = env.step(action)
    if done or truncated:
        obs, _ = env.reset()
env.close()
```