Robot positioning and mapping method, computer device and computer readable storage medium

Abstract

The invention provides a robot positioning and mapping method, a computer device and a computer readable storage medium. The method comprises the following steps of pre-integrating information acquired by an inertial measurement unit by utilizing information acquired by a camera device and information acquired by the inertial measurement unit; using the front end module to carry out motion tracking by utilizing pre-integrated relative pose information, and judge whether a visual tracking loss condition occurs or not, if the visual tracking loss condition does not occur, carrying out the visualand inertial measurement fusion operation, and updating the state information of an inertial measurement unit; and when a new key frame is generated, using the rear end module to acquire the pose information of the key frame acquired by the front end module and the corresponding relation information of the feature points, create and optimize a factor graph, and update a rear end map by using theacquired pose information and the depth information of the 3D points. The invention also provides a computer device for realizing the method and a computer readable storage medium. According to the invention, the positioning and mapping of the robot can be realized efficiently and accurately.

Description

technical field [0001] The present invention relates to the field of image processing, specifically, a sweeping robot positioning and mapping method based on monocular vision and an inertial measurement unit, and also relates to a computer device and a computer-readable storage medium for realizing the method. Background technique [0002] With the development of intelligent control technology, unmanned intelligent robots have begun to be widely used, such as transportation robots for industrial production applications, sweeping robots for household use, window cleaning robots, and small drones. Because these robots need to move during the working process, some robots need to move quickly. In order to realize the motion control of the robot, it is usually realized by using Simultaneous localization and mapping (SLAM) technology. [0003] Synchronous positioning and mapping technology is a technology for robots to simultaneously realize their own positioning and environment m...

AI Technical Summary

Problems solved by technology

The loose coupling framework is similar to the filter fusion method, but the accuracy is low; the tight coupling framework allows the data of the inertial measurement unit to correct the visual odometry, and the visual odometry information can also correct the zero offset of the inertial measurement unit, so The positioning accuracy of the tightly coupled framework is high, but the calculation is complex and accurate, and cannot be run in real time on platforms with low computing power such as embedded platforms

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