Abstract: A mapping method for a mobile robot includes: obtaining positions of particles corresponding to the mobile robot using a particle filtering approach; selecting one of the particles with a largest weight in a particle swarm corresponding to a current time point, performing position matching between the one of the particles and a historical trajectory formed by the one of the particles with the largest weight, and determining whether the positions of the particles corresponding to the mobile robot match positions of historical trajectory points of the mobile robot; in response to the positions of the particles corresponding to the mobile robot matching the positions of the historical trajectory points of the mobile robot, optimizing a trajectory of the mobile robot using a graph optimization approach; and building a map based on the optimized trajectory.

Abstract: The present disclosure provides localization methods and a system using the same. One of the methods includes: broadcasting a ranging frame in a awake state of a localization tag; obtaining a response frame returned by the first anchor according to the ranging frame; updating the ranging anchor list according to the response frame; and calculating a distance between the localization tag and the first anchor based on a time of broadcasting the ranging frame, a time of receiving the response frame, the time of the first anchor receiving the ranging frame, and the time of the first anchor transmitting the response frame. In such a manner, the localization tag is enabled to switch the anchor for ranging in time according to the updated ranging anchor list during movement, thereby automatically ranging with the nearby anchor.