Preprint
Aug 2026
Learning Fault-Tolerant Locomotion with Adaptive Gait Timing
A deep reinforcement learning approach for fault-tolerant locomotion under actuator power loss that employs an asymmetric actor-critic architecture in which the critic has access to privileged information during training, while the actor learns to reconstruct a corresponding latent representation from proprioceptive observations.
Giovanbattista Gravina, Luca Rossini, Carlo Rizzardo et al.
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