A Navigation Method for Semantic Slam Service Robot in Indoor Dynamic Environment

Abstract

The present invention provides a semantic SLAM service robot navigation method in an indoor dynamic environment, which includes the following steps: (1) information semantic segmentation and feature point extraction; (2) moving consistency check, eliminating dynamic points, and then using stable static Camera pose estimation by feature points; (3) Construction of semantic octree map; (4) Initialization of the service robot’s own pose; (5) Solving the optimal velocity trajectory through the DWA local path planning algorithm combined with the gray wolf optimization algorithm , to determine the driving path of the service robot... To solve the problem that the existing traditional SLAM scene cognitive ability is weak, which leads to the low positioning accuracy of the service robot and the local dynamic planning of the traditional DWA is easy to fall into the local optimal position. A combination of gray wolf optimization algorithm is proposed The DWA local path planning method combined with semantic information realizes dynamic obstacle avoidance, guarantees the cognitive ability of the service robot to the environment when it travels, can provide more accurate speed information, and increases safety and reliability at the same time.

Description

technical field [0001] The invention relates to a semantic SLAM service robot navigation method in an indoor dynamic environment, and relates to the field of autonomous navigation of service robots, in particular to the field of semantic SLAM service robot navigation methods. Background technique [0002] With the continuous improvement of living standards in contemporary society, people's demand for quality of life is also constantly improving, and various intelligent service robots continue to appear, and better research on service robots has become increasingly important. The SLAM method for mobile robots is the basis of intelligent service robots. The early traditional SLAM method was mainly based on the assumption of a static environment. In recent years, the emergence of artificial intelligence methods, especially machine learning methods, has significantly improved the performance of mobile robots in dynamic environments and greatly enhanced the ability to detect mova...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a semantic SLAM service robot navigation method in an indoor dynamic environment, which solves the weak cognitive ability of the existing traditional SLAM scene, which leads to the low positioning accuracy of the service robot and the partial dynamics of the traditional DWA. The planning is easy to fall into the problem of local optimal position. The DWA local path planning method combined with the gray wolf optimization algorithm is proposed, which combines semantic information to realize dynamic obstacle avoidance, guarantees the cognitive ability of the service robot to the environment when it travels, and can provide more accurate speed Information, increase safety and reliability at the same time, realize the pose estimation and effective planning of the route of the service robot in the dynamic environment, and also meet the real-time obstacle avoidance requirements of the service robot

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