Robot, map construction method, positioning method, electronic equipment and storage medium

Abstract

The invention provides a robot, a map construction method, a positioning method, electronic equipment and a storage medium. The map construction method of the robot includes the steps that the robot traverses a working region according to a preset rule, and an initial map is constructed according to images which are collected in real time when the robot traverses the working region, and comprisesa first map body and a second map body, wherein the first map body includes mapping of the working region and a map coordinate system, and the second map body includes extracted scene features based on the collected images and a geometric quantity of the scene features. The map is constructed without active signals by the adoption of a passive vision sensor, the vision sensor is low in power consumption and cost, the quantity of obtained signals is large, and the map construction of the intelligent robot is optimized.

Description

technical field [0001] The invention relates to the field of robots, in particular to a robot, a map construction method, a positioning method, electronic equipment, and a storage medium. Background technique [0002] At present, mobile robots, such as sweeping robots, have been accepted and actually used by more and more families. At present, the current common robot positioning and mapping rely on actively emitting signals, such as lasers, infrared, etc., to detect the external environment and then build maps. For example, the real-time positioning and map construction technology of some intelligent robots is FastSLAM. FastSLAM is generally implemented using a laser rangefinder or sonar. Due to the use of laser, sonar and other sensors, FastSLAM cannot recognize robots in special environments, and can only estimate the entire environment through pre-judgment. [0003] It can be seen that these methods cannot be applied in all environments, and the power consumption is h...

AI Technical Summary

Problems solved by technology

Due to the use of sensors such as lasers and sonar, FastSLAM cannot recognize robots in special environments, and can only estimate the entire environment through pre-judgment

[0003] It can be seen that these methods cannot be applied in all environments, and the power consumption is high, the cost is high, and the amount of information obtained is small, which limits the application of artificial intelligence in robots.

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