A method for positioning, comprising: acquiring a visual feature map of a geographic area located by a movable object, the visual feature map comprising a first set of visual features, and the first set of visual features comprising a first visual feature perpendicular to a road surface of the geographic area; acquiring at least one image (102; 400) captured by a camera coupled to the movable object during a motion of the movable object within the geographic area; extracting a second set of visual features corresponding to the first set of visual feature features from the at least one image (102; 400); and determining at least one pose of the movable object during the motion, at least based on the visual feature map and the second set of visual features; wherein determining the at least one pose of the movable object during the motion comprises: acquiring information related to the motion of the movable object; representing a plurality of possible poses of the movable object at a current moment during the motion, with a plurality of particles; determining a respective state and a respective weight of the plurality of particles at the current moment, based on the visual feature map, the second set of visual features and the information; the method further characterised by: clustering the plurality of particles into a plurality of clusters based on a distribution state of the plurality of particles; determining a sum of the weights of particles included in each cluster; and determining a pose of the movable object at the current moment based on a cluster having a maximum sum. acquiring a visual feature map of a geographic area located by a movable object, the visual feature map comprising a first set of visual features, and the first set of visual features comprising a first visual feature perpendicular to a road surface of the geographic area; acquiring at least one image (102; 400) captured by a camera coupled to the movable object during a motion of the movable object within the geographic area; extracting a second set of visual features corresponding to the first set of visual feature features from the at least one image (102; 400); and determining at least one pose of the movable object during the motion, at least based on the visual feature map and the second set of visual features; wherein determining the at least one pose of the movable object during the motion comprises: acquiring information related to the motion of the movable object; representing a plurality of possible poses of the movable object at a current moment during the motion, with a plurality of particles; determining a respective state and a respective weight of the plurality of particles at the current moment, based on the visual feature map, the second set of visual features and the information; the method further characterised by: clustering the plurality of particles into a plurality of clusters based on a distribution state of the plurality of particles; determining a sum of the weights of particles included in each cluster; and determining a pose of the movable object at the current moment based on a cluster having a maximum sum. acquiring information related to the motion of the movable object; representing a plurality of possible poses of the movable object at a current moment during the motion, with a plurality of particles; determining a respective state and a respective weight of the plurality of particles at the current moment, based on the visual feature map, the second set of visual features and the information; the method further characterised by: clustering the plurality of particles into a plurality of clusters based on a distribution state of the plurality of particles; determining a sum of the weights of particles included in each cluster; and determining a pose of the movable object at the current moment based on a cluster having a maximum sum. clustering the plurality of particles into a plurality of clusters based on a distribution state of the plurality of particles; determining a sum of the weights of particles included in each cluster; and determining a pose of the movable object at the current moment based on a cluster having a maximum sum.