Modern quadruped locomotion — RL pipeline.

hard

Answer

$(1) Massively parallel simulation (IsaacGym / Isaac Sim, MuJoCo MJX, Genesis) — thousands of robots in parallel on one GPU.$
$(2) PPO on domain-randomized environment (friction, mass, latency, terrain).$
$(3) Curriculum from flat to rough terrain.$
$(4) Reward shaping: forward velocity + energy efficiency + smoothness.$
$(5) Deploy zero-shot to real robot (Rudin et al. 2022, Anymal, Spot).$
$Trained in hours; robust real-world walking without fine-tuning.$

Check yourself — multiple choice

Random
Massively parallel sim (IsaacGym / MJX) + PPO + domain randomization + curriculum flat → rough terrain + reward shaping; zero-shot sim2real for Anymal / Spot in hours
Same as OpenAI Five
Not real

Quadruped RL: parallel sim + PPO + DR + curriculum → sim2real hours.

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