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SLAM back-end track optimizing method based on pose chain model

A trajectory optimization and pose technology, applied in two-dimensional position/channel control and other directions, can solve problems such as not having much value, and achieve the effect of reducing trajectory drift

Inactive Publication Date: 2017-10-20
SUN YAT SEN UNIV
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Problems solved by technology

The general SLAM back-end trajectory optimization algorithm is to obtain all the data obtained by the front-end and extract an objective function to be optimized according to the established factor graph or pose graph, and use the least squares algorithm to linearize the nonlinear equation to obtain an update Step size, this kind of algorithm belongs to offline optimization, and the difference between the real SLAM system and the general 3D reconstruction and positioning technology is that it can get real-time 3D mapping and accurate position of the surrounding environment when moving, so offline optimization It's just an afterthought solution, not of much value for real applications

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  • SLAM back-end track optimizing method based on pose chain model
  • SLAM back-end track optimizing method based on pose chain model
  • SLAM back-end track optimizing method based on pose chain model

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[0017] The accompanying drawings are for illustrative purposes only, and should not be construed as limitations on this patent; in order to better illustrate this embodiment, certain components in the accompanying drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art It is understandable that some well-known structures and descriptions thereof may be omitted in the drawings. The positional relationship described in the drawings is for illustrative purposes only, and should not be construed as a limitation on this patent.

[0018] Such as figure 1 As shown, the present invention adopts the pose chain SLAM back-end optimization model, and the characteristics of the model are: there is a strict timing relationship between nodes, and the graph model is relatively sparse.

[0019] The triangle represents the pose of the robot, and the edge represents the relative pose between connected poses. There are two ...

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Abstract

The invention relates to the technical field of a full automatic movement robot, and particularly to an SLAM back-end track optimizing method based on a pose chain model. An SLAM is thought as a key for realizing the full automatic movement robot and is mainly composed of a frontend preprocessing part and a backend optimizing part. The frontend preprocessing part supplies an initial estimated map and position information through analyzing and integrating various kinds of sensor data. The backend optimizing part utilizes a picture model for describing initial estimation and probability restriction and utilizes a most optimized method for optimizing the initial estimation for realizing higher-precision mapping and positioning. According to the method, the pose chain model with a restrict time sequence relation between nodes is introduced; a sparse characteristic of the pose chain model is utilized for settling a problem of online real-time optimization which cannot be realized by common SLAM backend optimization technology; furthermore a requirement for high application precision can be satisfied; and a quick and effective settling method is supplied for settling an SLAM backend optimizing problem.

Description

technical field [0001] The present invention relates to the technical field of fully autonomous mobile robots, and more specifically, to a SLAM back-end trajectory optimization method based on a pose chain model. Background technique [0002] SLAM (simultaneous positioning and mapping) is considered to be the key to realizing a truly fully autonomous mobile robot. It is mainly divided into two parts: front-end preprocessing and back-end optimization. Front-end preprocessing provides an initial estimate map by analyzing and synthesizing various sensor data. And location information, the back-end optimization is to use the graphical model to describe the initial estimate and probability constraints, and use the optimization method to optimize the initial estimate to achieve higher-precision mapping and positioning. The general SLAM back-end trajectory optimization algorithm is to obtain all the data obtained by the front-end and extract an objective function to be optimized ac...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 陈龙杨俊黎丹
Owner SUN YAT SEN UNIV
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