SLAM back-end trajectory optimization method based on loop detection

A trajectory optimization and loopback technology, applied in two-dimensional position/channel control, non-electric variable control, instruments, etc., can solve problems such as large amount of calculation, low optimization efficiency, large resource consumption, etc., to ensure accuracy and improve calculation. Efficiency, solve the effect of poor online real-time performance

Inactive Publication Date: 2019-02-15
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0010] The present invention provides a SLAM back-end trajectory optimization method based on loopback detection in order to overcome the defects of large amount of calculation, large resource consumption, and low optimization efficiency described in the above-mentioned prior art

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  • SLAM back-end trajectory optimization method based on loop detection
  • SLAM back-end trajectory optimization method based on loop detection
  • SLAM back-end trajectory optimization method based on loop detection

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[0050] The accompanying drawings are for illustrative purposes only and cannot be construed as limiting the patent;

[0051] In order to better illustrate this embodiment, some parts in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0052] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings.

[0053] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0054] This embodiment provides a SLAM back-end trajectory optimization method based on loop closure detection.

[0055] The method comprises the steps of:

[0056] S1: Obtain sensor data;

[0057] S2: Perform data processing on the data acquired by S1 to obtain the initial pose of the robot;

[0058] S3: Construct a pose graph model through the initial pose obtained in S2;

[0059] S4: Pe...

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Abstract

An SLAM back-end trajectory optimization method based on loop detection includes the following steps: S1, acquiring sensor data; S2, processing the data acquired in S1 to obtain the initial pose of arobot; S3, constructing a pose map model through the initial pose acquired in S2; S4, carrying out closed-loop detection on the pose map model constructed in S3, and separating the closed-loop part and the non-closed-loop part of the pose map model; and S5, optimizing the different parts after detection separately. Each time a closed loop is detected, optimization is carried out. Each time a closed loop appears, the total error of the closed-loop part is calculated, and then, the total error of the non-closed-loop part is calculated. The weight information of edges in the data provided by thefront end is utilized reasonably, and a kernel function (Huber kernel) is added. The pose error can be allocated quickly and effectively, the calculation efficiency can be improved, and the online real-time performance of the back-end optimization process of the robot can be enhanced. Moreover, the accuracy can be ensured.

Description

technical field [0001] The invention relates to the field of fully automatic self-service mobile robots, and more specifically, to a SLAM back-end trajectory optimization method based on loop closure detection. Background technique [0002] Simultaneous Location and Mapping (SLAM for short) is to use the sensors carried by the robot itself to obtain the information of the environment in which it is located to estimate the pose of the robot and build an environmental map. It is the key technology for the robot to move completely autonomously; Estimation problems can be divided into filtering methods and smoothing methods according to estimation techniques. [0003] Common filtering methods include extended Kalman filter EKF (extended Kalman filters), sparse extended information filter EKFs, particle filter, etc.; at the beginning, SLAM based on graph optimization was considered to be very time-consuming. With the development of some open source sparse matrix operation algorit...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0221G05D2201/0217
Inventor 廖仕良高军礼彭世国郭靖
Owner GUANGDONG UNIV OF TECH
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