Robot Applications

Manipulation

Grasping

• SAC for 6-DOF grasp learning
• Image-based policy
• Curriculum learning

In-hand Manipulation

• Dexterous hand control
• DAPG (Dagger)

Locomotion

Walking

• PPO for quadruped control
• Reward shaping
• Domain randomization

Swimming/Flying

• Sim-to-real challenges
• Residual policies

Best Practices

1. Curriculum learning: Start simple, increase difficulty
2. Observation normalization: Improve training stability
3. Action scaling: Match environment limits
4. Domain randomization: Bridge sim-to-real gap

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