A robot learning from demonstration method based on meta-imitation learning. The method includes: obtaining robot demonstration and teaching task set; constructing a network structure model to adapt the objective loss function; in a meta-training stage, using Algorithm 1 to learn and optimize the adaptive objective loss function, and then obtaining the strategy parameters; in a meta-testing stage, using Algorithm 2 to learn the trajectory demonstrated to obtain the learning strategy; taking the expert's demonstration trajectory as input, combining the learned strategy to generate the robot simulation trajectory, mapping to the robot's actions. The method can quickly generalize to new scenes from a small number of demonstration examples given by expert's demonstration without specific task engineering. In addition, the robot can self-learn strategies that have nothing to do with the task by the expert's demonstration, thereby generating a trajectory and realizing a demonstration and rapid teaching.
ROBOT LEARNING FROM DEMONSTRATION VIA META-IMITATION LEARNING