1. A collaboration method for spatial navigation, comprising steps of: providing a plurality of entities, wherein each entity communicates with the other entities, and each entity shares spatial navigation information with the other entities; generating a first possible match portion by comparing topological order similarity between a first self-map for a first entity and at least one self-map for at least one other entity; constructing a virtual self-map for each entity, wherein the self-map and at least one cognitive map received form at least one other entity are overlapped to be the virtual self-map by combining at least one first possible match portion between the self-map and at least one cognitive map when a confidence index of the cognitive map is no less than a threshold value; and constructing a virtual whole map, by repeating the step of constructing the virtual self-map to form the virtual whole map for a specific space, wherein the step of generating a first possible match portion by comparing topological order similarity comprises steps of: determining an origin and two or more feature points on key features on the first self-map; selecting a coordinate system to determine a position of each feature point in the first self-map, wherein the position of each feature point is determined by at least two parameters according to the dimensions of the first self-map; establishing a topological relationship in each dimension between the feature points on the key features; and utilizing the topological relationship in each dimension between the feature points to generate the first possible match portion, wherein the step of establishing a topological relationship in each dimension between the feature points on the key features comprises steps of calculating and sorting topological distances between each feature points and the origin to produce one or more sequences according to the dimension of the image, and the sequence at least includes a first sequence related to a first parameter between the origin and each feature points, and a second sequence related to a second parameter between the origin and each feature points in the first self-map.