Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning

Legged robots can traverse hazardous environments, but current locomotion controllers do not explicitly model the risks associated with their actions. This work proposes a risk-sensitive locomotion training method using distributional reinforcement learning to consider safety explicitly.