Gmapping mapping method of mobile robot based on sparse pose adjustment

A mobile robot and posture adjustment technology, applied in the field of robotics, can solve problems such as complex environments and noise interference

Active Publication Date: 2020-07-17
BEIJING UNIV OF CIVIL ENG & ARCHITECTURE
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] Because the Gmapping-SLAM algorithm has a complex environment, when the odometer receives noise i...

Method used

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  • Gmapping mapping method of mobile robot based on sparse pose adjustment
  • Gmapping mapping method of mobile robot based on sparse pose adjustment
  • Gmapping mapping method of mobile robot based on sparse pose adjustment

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Experimental program
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Embodiment 1

[0060] This embodiment provides a Gmapping mapping method for mobile robots based on sparse pose adjustment, such as figure 1 As shown, the steps include:

[0061] S1: Initialize the particle pose and distribution, and pass the robot pose of the i-th particle at the previous moment with odometer information Estimate the robot's estimated pose of the i-th particle at this moment , calculate the proposed distribution p;

[0062] S2: Based on map information , robot estimated pose , observation , matching the estimated pose of the robot scanning the i-th particle the surrounding area;

[0063] If the scan matching is successful, enter S3 to calculate the maximum likelihood estimation value of the robot pose ; And judge whether to start the linear optimization thread, if start the linear optimization process, then execute S3 and S3'; otherwise, only execute S3;

[0064] If the scan matching fails, skip S3 and S4 and calculate the pose of the robot , update the w...

Embodiment 2

[0109] On the basis of Embodiment 1, this embodiment further provides a Gmapping method for mobile robots based on sparse pose adjustment, such as figure 2 - as shown in Figure 6(b).

[0110] Currently, all lidar 2D SLAM algorithms rely on probabilistic models in the map construction process, which is essentially a state estimation problem for mobile robots. The advantage of applying a probability model is that it can enhance the robustness of the system to observation noise and the ability of the system to formally express its uncertainty in the process of measurement and estimation. The lidar 2DSLAM (2-dimensional planar simultaneous positioning and mapping method) based on the probability model mainly relies on Bayesian theorem to solve. Filter-based SLAM can be mainly divided into SLAM based on Kalman filter KF (Kalman filters) and SLAM method based on particle filter PF (Particle filters).

[0111]The KF filter is one of the successful implementations of the Bayesian f...

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Abstract

The invention relates to the field of robots, and particularly provides a Gmapping mapping method of a mobile robot based on sparse pose adjustment, which comprises the following steps of S1, initializing particle poses and distribution, S2, scanning and matching, S3, calculating target distribution of sampling positions, S4, calculating Gaussian approximation, S5, updating the weight of the ith particle, and S6, updating the particle map. S3'pose map construction and S4' closed-loop constraint are implemented simultaneously with S3 and S4. According to the method, the technical problems of fuzzy boundaries, missing and slippage of an original Gmapping algorithm under the condition of few particles are solved, the construction precision is high, the boundaries are clear and complete, and the stability is good.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a Gmapping method for mobile robots based on sparse pose adjustment. Background technique [0002] In recent years, with the introduction of concepts such as "Industry 4.0", "Intelligent Manufacturing" and "Made in China 2025", the field of robotics has made great progress and vigorous development. In the field of service robots, the research on indoor mobile robots has become a hot issue. At present, the research on indoor mobile robots mainly focuses on map construction, positioning, navigation, etc., that is, to solve the problems of "who am I", "where am I" and "where am I going" for mobile robots. However, the above problems do not exist in isolation. Accurate map construction in an unknown environment depends on accurate positioning information, and precise positioning depends on accurate mapping. The autonomous navigation and path planning of mobile robots depend on accura...

Claims

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Application Information

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IPC IPC(8): G05D1/02G01C21/20G01S17/89
CPCG01C21/206G01S17/89G05D1/0221G05D1/0223G05D1/0253G05D1/0257G05D1/0276G05D2201/02
Inventor 赵光哲陶永江山
Owner BEIJING UNIV OF CIVIL ENG & ARCHITECTURE
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