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Method for autonomous navigation and positioning underwater

An autonomous navigation and pose technology, applied in navigation computing tools and other directions, can solve problems such as complex calculations, low data association accuracy, and insufficient prior information, and achieve the effect of improving computing speed

Active Publication Date: 2017-02-15
JIANGSU UNIV OF SCI & TECH
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Problems solved by technology

[0004] Purpose of the invention: In order to overcome the shortcomings of the existing traditional SLAM methods in the dense clutter and underwater environment with a large number of features and drastic changes, the shortcomings of low data association accuracy and complex calculations and the lack of prior information in the existing random finite set SLAM method Problem, the present invention provides a method for underwater autonomous navigation and positioning with high data association accuracy and simple calculation

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  • Method for autonomous navigation and positioning underwater
  • Method for autonomous navigation and positioning underwater
  • Method for autonomous navigation and positioning underwater

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Embodiment Construction

[0022] The present invention will be further explained below in conjunction with the accompanying drawings.

[0023] Such as figure 1 As shown, a method for underwater autonomous navigation and positioning disclosed by the present invention mainly includes the following steps:

[0024] Step 1. Model the feature information of the map at time k fed back by the robot, the observation information of the map feature, and the probability of missed detection caused by sensor uncertainty into a random finite set form. The number of map feature sets varies from zero to arbitrary size, and increases monotonously with the map features that appear in the robot's field of vision continuously, and each map feature is independent of each other.

[0025] M = φ (no map features)

[0026] M={m 1}(a state is m 1 map features)

[0027] M={m 1 ,m 2}(two map features m 1 ≠m 2 )

[0028] M={m 1 ,...,m n}(n map features m 1 ≠...≠m n )

[0029] In the SLAM process, the map feature obse...

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Abstract

The invention discloses a method for autonomous navigation and positioning underwater and belongs to the field of autonomous navigation of an underwater robot. The method uses a random finite set method to realize modeling of a SLAM problem so that the map feature information, map feature observation Information and clutter can be accurately described. In the aspect of map feature estimation, a new mapping information mixing method improves the shortcomings of the prior information of a PHD filter in the prediction phase and improves map feature number and map feature position estimation precision of the traditional probability hypothesis density-synchronous localization and mapping (PHD SLAM) method. In the aspect of robot pose estimation, an empty map feature strategy is used to improve a computing speed of robot pose estimation.

Description

technical field [0001] The invention belongs to the field of autonomous navigation of underwater robots, in particular to a method for autonomous underwater navigation and positioning. Background technique [0002] Underwater autonomous navigation and positioning are mainly realized by robots. The traditional SLAM (Simultaneous Localization and Mapping, hereinafter referred to as SLAM) method used in robots currently has data in dense clutter and underwater environments with a large number of features and drastic changes. The problem of low correlation accuracy and complex calculation, and in the process of SLAM implementation, due to the error in the process of robot movement, the observation error of the sensor, and the lack of detection of map features caused by the uncertainty of the sensor, will affect the data association process. Accuracy, so the accuracy of traditional SLAM methods is very sensitive to the data association of map feature information. [0003] The pr...

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 章飞史剑鸣孙陶莹曾庆军
Owner JIANGSU UNIV OF SCI & TECH
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