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Autonomous exploration type semantic map construction method and system

A semantic map and construction method technology, applied in two-dimensional position/channel control and other directions, can solve problems such as inability to obtain object attributes, difficulty in fully understanding scene information, etc., to improve autonomy and intelligence, efficient exploration, and speed. Effect

Pending Publication Date: 2022-08-02
XIAN UNIV OF TECH
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Problems solved by technology

The mobile robot can use the SLAM algorithm to accurately estimate its own position and understand the geometric structure information in the environment, but it cannot obtain information such as the attributes of objects in the space, making it difficult to fully understand the scene information

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  • Autonomous exploration type semantic map construction method and system
  • Autonomous exploration type semantic map construction method and system
  • Autonomous exploration type semantic map construction method and system

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Embodiment Construction

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings, which are to explain rather than limit the present invention.

[0040] see Figure 1-6 , an autonomous exploratory semantic map construction method, including the following steps:

[0041] Step 1, the mobile robot autonomously explores the unknown environment based on the improved and rapidly expanding random tree autonomous exploration algorithm to obtain the frontier point of the target scene. The specific method is as follows:

[0042] S1.1) Scan the environment with Rplidar lidar and mark the explored area as 0, the unexplored area as -1, and the obstacle as 1.

[0043] S1.2) Initialize random tree and take random sampling point x rand , and find the closest point x in the random tree to the randomly taken point nearest . Then, extend a fixed length from the nearest point to the random sampling point to get a new point x new . Then, if x nearest with...

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Abstract

The invention discloses an autonomous exploration type semantic map construction method and system, and the method comprises the steps: carrying out the autonomous exploration of an unknown environment based on a robot autonomous exploration algorithm of an improved rapid extension random tree, and carrying out the global front point detection and local front point detection through employing a global random tree and a local random tree in the exploration process; clustering the front edge points after the front edge points are obtained, selecting the front edge point with the maximum income as an optimal target point, and controlling the robot to arrive at the optimal target point along the optimal path; an image sequence of a current scene is collected in the moving process of the robot, the position of the robot is continuously updated, and when the optimal target point changes, the path is re-planned, and the robot is controlled to reach a new optimal target point; according to the method, the RGB image collected in the autonomous exploration process of the robot is subjected to semantic segmentation, and the RGB image and the corresponding depth map are combined to serve as input of the semantic map construction system, so that the autonomous semantic map construction task is completed, and the autonomy and intelligence of the robot are improved.

Description

technical field [0001] The invention relates to the technical field of indoor navigation of mobile robots, in particular to a method and system for constructing an autonomous exploratory semantic map. Background technique [0002] As a representative of future high-tech, robotics is not only the key to the upgrading of traditional manufacturing industries, but also the cornerstone of the development of emerging industries. It is of great significance for promoting intelligent manufacturing, improving production efficiency and improving people's livelihood. Among them, mobile robots have attracted the attention of many scholars due to their high autonomy and intelligence, but the construction of target scene maps is still an important research content for autonomous navigation of mobile robots. Autonomous navigation of robots in unknown environments has important application value. [0003] The mobile robot moves in an unknown environment without any prior information, obtai...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/024G05D1/0221G05D1/0276
Inventor 辛菁冯佳乐刘丁岳鹏宇思荣轩
Owner XIAN UNIV OF TECH
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