Abstract: A point cloud positioning error detection method, performed by a processing device, includes: obtaining a plurality of pieces of first point data and a target point cloud map, wherein the target point cloud map includes a plurality of pieces of target point data, registering the first point data and the target point data to obtain a plurality of pieces of second point data, selecting a plurality of pieces of third point data from the second point data according to a first default distance, calculating a plurality of matching scores of the third point data relative to the target point data, obtaining a plurality of step vectors corresponding to the third point data, respectively, when said registering converges, and obtaining a plurality of effective values according to directions of the step vectors, and outputting a localization fault detection result based on an intersection of the matching scores and the effective values.

Abstract: A navigation and positioning device including a storage, a mark feature analyzer, a first coordinate fusion component and a second coordinate fusion component is provided. The storage stores map information including a traffic mark feature and its mark coordinate. The mark feature analyzer is used for analyzing whether a captured image has the traffic mark feature. When the captured image has the traffic mark feature, the mark feature analyzer analyzes the traffic mark feature in the captured image and calculates a device coordinate according to the mark coordinate. The first coordinate fusion component fuses the device coordinate and a first fusion coordinate and uses fused coordinate as a second fusion coordinate. The second coordinate fusion component fuses the second fusion coordinate, traffic carrier inertial information and a global positioning coordinate and uses fused coordinate as an updated first fusion coordinate.

Abstract: A navigation and positioning device including a storage, a mark feature analyzer, a first coordinate fusion component and a second coordinate fusion component is provided. The storage stores map information including a traffic mark feature and its mark coordinate. The mark feature analyzer is used for analyzing whether a captured image has the traffic mark feature. When the captured image has the traffic mark feature, the mark feature analyzer analyzes the traffic mark feature in the captured image and calculates a device coordinate according to the mark coordinate. The first coordinate fusion component fuses the device coordinate and a first fusion coordinate and uses fused coordinate as a second fusion coordinate. The second coordinate fusion component fuses the second fusion coordinate, traffic carrier inertial information and a global positioning coordinate and uses fused coordinate as an updated first fusion coordinate.