Intelligent vehicular vision device based on ground texture and global localization method thereof

Abstract

This invention relates to mobile robot technique based on earth seam intelligent car visual device and its whole layout position method, which comprises the following steps: a, establishing environment layout earth seam map into system; b, sending the caught image signals by data line or collection program into top layer process unit; c, top layer process unit processes images to extract image seam information to form one local earth seam map; d, using intelligent mile information to reduce local map index range; e, searching the current local earth map and whole earth seam map.

Description

technical field [0001] The invention relates to a device and a method in the field of mobile robot technology, in particular to a ground texture-based smart car vision device and a global positioning method thereof. Background technique [0002] The self-localization problem of smart cars means that smart cars use sensor information to estimate their own pose (position and attitude) in the operating environment. The first thing encountered in practical application is the positioning problem, which is the premise of realizing smart car navigation. At present, the main positioning methods include positioning based on magnetic signals and positioning based on vision. Positioning based on magnetic signals is a relatively mature positioning method at present, but this method needs to bury sensing devices (such as energized wires or magnetic nails) in the operating environment. The system implementation process is cumbersome and difficult to maintain. When changing the operating ...

AI Technical Summary

Problems solved by technology

Therefore, if it is in a relatively complex outdoor environment, feature extraction is more difficult, the method described in the article is not applicable

and the text does not mention the robustness of the method to environmental changes

[0005] Another major problem with vision-based methods is that when environmental conditions such as lighting and shadows change or when the front of the camera is blocked, the system is likely to fail to operate normally, that is, it cannot show strong robustness to environmental changes.

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