Linear segment feature-based high-precision carrying robot positioning and navigating method

A positioning navigation and robot technology, applied in the field of high-precision positioning and navigation of transport robots, can solve the problems of large accumulated errors, laser radar online scanning interference, inability to apply precision, accuracy in industrial fields, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2018-10-26
苏州中研讯科智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in the industrial environment, the texture of the scene is single, and it is difficult to establish stable image feature points, so the visual slam is not suitable for the industrial scene; the laser radar inevitably leads to measurement errors of the point cloud due to online scanning interference and its own accuracy.
[0005] In addition, the current laser SLAM technology uses laser radar + front-end ICP matching + back-end optimization algorithm to accumulate large errors, resulting in low positioning accuracy and map construction accuracy, which cannot be applied to industrial fields that require high precision and accuracy.

Method used

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  • Linear segment feature-based high-precision carrying robot positioning and navigating method
  • Linear segment feature-based high-precision carrying robot positioning and navigating method
  • Linear segment feature-based high-precision carrying robot positioning and navigating method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0074] This embodiment shows a high-precision positioning and navigation method for a carrier robot based on straight line features, including the following steps:

[0075] S1) Dynamic model of autonomous positioning and navigation car:

[0076] (1)

[0077] (2)

[0078] (3)

[0079] (4)

[0080] (5)

[0081] The position of the trolley center O’ at the next moment is obtained by using the second-order Runge-Kutta iterative formula (Formula 6):

[0082] (6)

[0083] refer to figure 1 ,in, L and R represent the angular velocity of the left wheel and the right wheel respectively, v L and v R Represent the linear velocity of the left wheel and the right wheel respectively, and v represent the linear velocity of the center O' of the trolley, E is the rotational angular velocity of the trolley, r is the radius of the trolley wheel, L is the distance between the two wheels, G is the angular velocity measured by the gyroscope;

[0084] S2) Use t...

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PUM

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Abstract

The invention provides a linear segment feature-based high-precision carrying robot positioning and navigating method. Regarding the indoor application characteristics of an industrial carrying robot,a linear segment is used as a graph building feature instead of traditional dots, world coordinates of the linear segment are calculated by the environment measured by laser radar or distance and angle of a barrier, and the least squares are taken as approximation of the linear segment, so that measurement errors can be eliminated, the status dimension of the system can be reduced, and the operation speed can be improved; the correlation between current measurement and built graph data is utilized, and the running state of a robot is further precisely estimated by an extended Kalman filter algorithm, so that the positioning accuracy and reliability of the system can be improved for the second time.

Description

technical field [0001] The present invention relates to intelligent control technology, in particular to the field of AGV intelligent control technology. Specifically, it shows a high-precision positioning and navigation method for a carrier robot based on the characteristics of a straight line segment. Background technique [0002] SLAM technology, that is, real-time positioning and map construction, is the core of AGV intelligent control technology and is widely used in VR / AR, drones, unmanned driving, robot positioning and navigation and other fields. [0003] SLAM is mainly divided into two types: laser slam and visual slam; two methods are widely used in the field of positioning and navigation. [0004] However, in an industrial environment, the texture of the site is single, and it is difficult to establish stable image feature points, so visual slam is not suitable for industrial sites; due to online scanning interference and its own accuracy, laser radar inevitably l...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/206
Inventor 倪涛李文航
Owner 苏州中研讯科智能科技有限公司
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