Visual SLAM method suitable for indoor dynamic environment

Abstract

The invention relates to a visual SLAM method suitable for an indoor dynamic environment, and the method comprises the steps of obtaining a color image packaging frame of the environment, calculatinga dynamic probability propagation result, removing dynamic feature points according to the dynamic probability, reserving static feature points, and carrying out the target detection of a key frame ifa current frame meets a key frame condition during the judgment of the key frame; performing semantic segmentation on the picture according to a detection result, determining an area belonging to a dynamic object, updating a dynamic probability of a map point corresponding to the feature point of the key frame, inputting a local mapping thread, updating and extracting a local common view, performing local optimization on the poses of the key frame and the map point, and updating an essential diagram to perform global optimization. When pose calculation and map construction are carried out, object category information in the environment is effectively fused, a target detection algorithm is fused with a traditional visual SLAM system, feature points belonging to a dynamic object are removedin time, and the positioning and mapping accuracy and robustness are higher in the dynamic environment.

Description

technical field [0001] The invention belongs to the technical field of robotics and computer vision, and in particular relates to a visual SLAM method suitable for indoor dynamic environments. Background technique [0002] SLAM (simultaneous localization and mapping), real-time positioning and map construction, or concurrent mapping and positioning. The robot starts to move from an unknown position in an unknown environment, and locates itself according to position estimation and maps during the movement process. At the same time, an incremental map is built on the basis of its own positioning to realize the autonomous positioning and navigation of the robot. [0003] Visual SLAM technology enables the subject equipped with the camera sensor to complete the establishment of the environment model and the estimation of its own motion state during the movement of the subject without prior information of the environment. In today's social life, visual SLAM systems are widely us...

AI Technical Summary

Problems solved by technology

Such a classic visual SLAM framework can obtain good experimental results in static scenes, but when the scene contains dynamic object information, such as people walking and moving cars in the scene, the classic visual SLAM framework still takes these dynamic objects into account. The object is in a static state by default, and the feature points in the dynamic object area in the scene cannot be removed in time. If the feature points extracted from the dynamic object are also included under the conditions of geometric constraints and graph optimization constraints, a large error will occur in the SLAM system

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