The invention brings forward a mobile robot continuous control method based on a non-map motion planner. Main contents of the method comprise the non-map motion planner, an asynchronous depth determination strategy gradient, reinforcement learning, an assessment network and a reward function. The process of the method is as follows: end-to-end training is performed by utilizing the non-map motion planner, and a transition function is found for the non-map motion planner in order to control frequency; an original depth is modified, and a strategy gradient is determined to be the asynchronous depth determination strategy gradient; the reinforcement learning is performed so that training and sample collection can be executed in parallel; and the motion planner is assessed by utilizing the assessment network, the reward function is defined, and whether a target is reached is checked. A high-precision laser range-finding sensor is used, a path can be accurately calculated, and efficiency is high; and any manual design and demonstration in advance are not needed, a feasible optimized path can be efficiently searched out, a robot is navigated to a target position, and the robot cannot collide with an obstacle in environment.