The invention discloses a
robot gait training method and
system based on
reinforcement learning, and relates to the technical field of
electric vehicle charging, and the method comprises the steps: carrying out the
simulation learning initialization of a strategy based on a reference video; selecting a plurality of evaluation indexes to design a dynamic reward function so as to guide the initial strategy network to optimize the
gait performance; through an environment difficulty scheduling mechanism, the training environment difficulty is automatically adjusted according to strategy performance; performing optimization training on the strategy network by using a PPO
algorithm; and judging the optimized
gait strategy by constructing a
cognitive load index, and outputting a final gait strategy. According to the method,
imitation learning, self-adaptive reward modeling, multi-stage scheduling,
reinforcement learning optimization and cognitive feedback are organically fused, and a
robot gait training framework with generalization ability, stability and social adaptability is constructed. According to the method, the naturalness, the stability and the man-
machine friendliness of the gait of the
robot can be remarkably improved under complex terrains and interaction scenes, and the method has wide application prospects and popularization value.