The invention discloses a distributed multi-robot navigation method which comprises the following steps: pre-deploying a trained navigation neural network model on each robot, and navigating the movement of each robot in a distributed non-communication environment through the navigation neural network model on the basis of sensor sensing data of the respective robot, wherein the training of the navigation neural network model is simulation movement training of deep learning in a simulation training scene according to a grid map formed by sensor perception data of a robot. According to the method, a navigation neural network model trained by deep reinforcement learning is deployed on a robot, a grid map is generated by various sensor information, and a local grid map taking the robot as a center is used as network input, so that the method has the advantages of strong anti-noise capability, low calculation cost and the like. In combination with a global path planner, collision-free mobile navigation can be performed on the robot in a distributed communication-free environment, and the method can be applied to various robot navigation scenes.
Distributed multi-robot navigation method