Robot autonomous localization and navigation based on image-text recognition and semantic meaning

Abstract

The invention relates to autonomous localization and navigation of mobile intelligent equipment such as service robots, unmanned aerial vehicles, automatic guided vehicles and indoor three-dimensionalmodeling equipment. Compared with the existing system, image-text recognition and semantic binding for indoor symbols are introduced. The characteristics are that (1) the recognized result of image-text recognition is high in accuracy compared with laser radar or road signs for visual recognition; (2) only a camera is required to be added, and the cost and the weight are low; (3) an accumulativeerror of sensors (an IMU, laser radar, vision, etc.) is effectively eliminated, and the accuracy of loop detection is improved; (4) the robot localization and navigation accuracy is improved on the whole by combining image-text recognition, and commercial use of robots is enabled to become possible; and (5) tool software provided by using the method combines a result of image-text recognition, endows an environment map with semantic information through manual binding, can promote man-machine communication and helps the robots to complete advanced tasks.

Description

technical field [0001] The present invention relates to the field of autonomous positioning and navigation of mobile smart devices such as service robots, unmanned aerial vehicles, automatic guided vehicles, and indoor 3D modeling equipment, and in particular to the positioning and navigation of smart mobile devices when there is no GPS signal indoors , this kind of positioning and navigation does not need to provide the floor plan of the environment in advance, and does not need to deploy wireless networks such as UWB and ZIGBEE networks indoors. Background technique [0002] The demand for high-precision positioning comes from the booming and rapidly developing field of robots and wearable devices. For example, robots include housekeeping robots, sweeping robots, and logistics robots. Compared with human positioning, positioning is just needed for these devices, and The diversity of application scenarios cannot be realized by special equipment such as UWB base stations and...

AI Technical Summary

Problems solved by technology

[0015] In the SLAM system based on vision or lidar, due to the error accumulation of the sensor and the error accumulation in the visual image matching, the position and trajectory of the robot often drift, so that after the robot moves for a short time or after moving a small area, the error is already Can not support its autonomous navigation and navigation

In SLAM, in order to overcome this problem, a loop closure technology is provided to overcome the invalid positioning caused by the complexity of the environment and the accumulation of sensor errors. However, one robot does not necessarily have to follow a closed route, and the other robot does not It must be able to maintain a certain positioning effectiveness before the effective loop detection (that is, it has "flyed" before the loop detection)

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