A path optimization method for an unmanned aerial vehicle (102). The method comprises: obtaining status data and action decision-making data of an unmanned aerial vehicle (102) during a flight thereof (202); determining, according to the status data and the action decision-making data of the unmanned aerial vehicle (102), the instantaneous energy efficiency of the unmanned aerial vehicle (102) (204); training a pre-built deep reinforcement learning network (1064) using the status data as input, the action decision-making data as output, and the instantaneous energy efficiency as a reward, and optimizing a policy parameter of the deep reinforcement learning network (1064) (206); and outputting, according to the trained deep reinforcement learning network (1064), a flight policy of the unmanned aerial vehicle (102) (208). Further provided are a path optimization device (106) for an unmanned aerial vehicle, and a computer-readable storage medium (704).
PATH OPTIMIZATION METHOD AND DEVICE FOR UNMANNED AERIAL VEHICLE, AND STORAGE MEDIUM