Bridging the Gap: Enabling Soft Actor Critic for High Performance Legged Locomotion 事件

Bridging the Gap: Enabling Soft Actor Critic for High Performance Legged Locomotion arXiv:2605.24975v1 Announce Type: cross Abstract: Proximal Policy Optimization (PPO) has become the de facto standard for training legged robots, thanks to its robustness and scalability in massively parallel simulation environments like IsaacLab. However, its on-policy nature makes it inherently sample-inefficient, preventing its use for continuous adaptation and fine-tuning on real hardware. Soft Actor-Critic