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4.4 Sim-to-real transfer techniques

Topic: Sim-to-Real Transfer Techniques​

📘 Chapter: Sim-to-Real Transfer Techniques

Robotics mein simulation (Sim) se real robot (Real) par trained model transfer karna ek major challenge hota hai. Isko Sim-to-Real Transfer kaha jata hai.

NVIDIA Isaac Sim is field ko accelerate karta hai high-fidelity physics, sensor simulation, aur domain randomization ke through.

🧠 1. What is Sim-to-Real?

Simulation mein robot safely aur fast training karta hai. Lekin real world unpredictable hota hai.

Sim-to-Real ka matlab: "Simulation mein trained model ko real hardware par successfully run karwana."

Challenges:

  • Real sensor noise
  • Real friction differences
  • Lighting changes
  • Timing & latency issues

🚀 2. Why Sim-to-Real is Important?

  • Simulation = safe, cheap, fast training
  • Real world = expensive, slow, risky
  • Bina Sim-to-Real techniques ke model real hardware par fail ho sakta hai.

Sim-to-Real ensures:

  • Transferable control policies
  • Reliable robot behavior
  • Faster development cycles

🌀 3. Sim-to-Real Workflow (Diagram)

        +----------------------------+
        |      Simulation (Isaac)     |
        |  - Physics Engine           |
        |  - Sensors Simulation       |
        |  - Domain Randomization     |
        +-------------+--------------+
                      |
                      v
        +----------------------------+
        | Train AI Model (RL/NN)      |
        +-------------+--------------+
                      |
                      v
        +----------------------------+
        | Export Policy / Model       |
        |  - ONNX / TensorRT          |
        +-------------+--------------+
                      |
                      v
        +----------------------------+
        | Deploy to Real Robot        |
        |  - Jetson / ROS 2           |
        |  - Real Sensors             |
        +-------------+--------------+
                      |
                      v
        +----------------------------+
        | Validation & Fine-Tuning    |
        +----------------------------+

🧩 4. Key Sim-to-Real Techniques

✅ 1. Domain Randomization​

Simulation parameters randomize kiye jate hain:

  • Lighting
  • Texture
  • Object shapes & colors
  • Physics variations
  • Sensor noise

Model robust ban jata hai unpredictable real world ke liye.

✅ 2. High-Fidelity Sensor Simulation​

Isaac Sim support:

  • RGB Camera
  • Depth Camera
  • LiDAR
  • IMU
  • Real physics-based noise modeling

✅ 3. Physics Parameter Tuning​

Real friction, mass, damping, torque limits ko match karna.

Isaac PhysX engine helps:

  • Accurate rigid body simulation
  • Constraint-based robotics

✅ 4. System Identification​

Real robot ki measurements lekar simulation ko match kiya jata hai.

  • Motors
  • Joint friction
  • Payload mass

✅ 5. Policy Fine-Tuning on Real Robot​

Sim-trained model ko thoda real robot par fine-tune kiya jata hai.

🤖 5. Example: Pick-And-Place Sim-to-Real

Simulation mein trained robotic arm:

  • Real object grip difference
  • Lighting change

Domain randomization → Model real world me stable ban jata hai.

🧪 6. Example Code (Conceptual Pseudocode)

from isaacsim import Randomizer
from rl import PPO

# Add domain randomization
domain = Randomizer()
domain.randomize_lighting()
domain.randomize_textures()
domain.randomize_physics()

env.apply_randomization(domain)

# Train policy
model = PPO(env)
model.train(steps=500000)

# Export for real robot
model.export("policy.onnx")

📝 7. Self Assignment

Assignment Tasks:​

  1. Isaac Sim install kar ke ek simple environment banao.
  2. Domain Randomization enable karo:
    • lighting
    • camera noise
  3. RL model (PPO) ko train karo.
  4. Model ko ONNX format mein export karo.
  5. Short report likho: Sim vs Real behavior comparison.

❓ 8. MCQs

Q1. Sim-to-Real ka main goal kya hota hai?​

A. Simulation ko slower banana
B. Real world me trained model ko deploy karna
C. Robot ko decorate karna

Q2. Domain Randomization kis cheez ko vary karta hai?​

A. Textures and lighting
B. Robot battery
C. Background music

Q3. Isaac Sim ka physics engine kaunsa hai?​

A. PhysX
B. Unreal Engine
C. Blender Physics

Q4. ONNX kis ka format hota hai?​

A. Game file
B. Neural network model export
C. Audio file

Q5. System Identification kya karta hai?​

A. Random jokes generate
B. Real robot parameters ko measure karta hai
C. Wi-Fi speed increase karta hai

✅ Correct Answers (MCQ Key)

  1. B
  2. A
  3. A
  4. B
  5. B