RANDPOL achieves effective quadruped locomotion by training only the final linear readout of a randomly initialized and fixed neural network policy, matching PPO results with reduced parameters and enabling zero-shot sim-to-real transfer on Unitree Go2.
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RANDPOL: Parameter-Efficient End-to-End Quadruped Locomotion via Randomized Policy Learning
RANDPOL achieves effective quadruped locomotion by training only the final linear readout of a randomly initialized and fixed neural network policy, matching PPO results with reduced parameters and enabling zero-shot sim-to-real transfer on Unitree Go2.