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Square root UKF calculation method based on standard deviation variable-scale sampling

A standard deviation and calculation method technology, applied in the direction of impedance network, digital technology network, electrical components, etc., can solve problems such as unstable calculation performance

Pending Publication Date: 2020-11-24
ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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Problems solved by technology

[0003] Aiming at the technical problem of unstable calculation performance in the existing UKF algorithm, the present invention proposes a square root UKF calculation method based on standard deviation variable-scale sampling, which introduces the estimated deviation of the traditional UKF algorithm into the UT transformation process, and based on statistical linearization Using the standard deviation calculation data of the optimal estimated deviation, the deterministic sampling points and their weight coefficients are designed, so as to construct a new UKF algorithm based on the standard deviation sampling strategy, and apply it to the state parameters of the autonomous mobile robot system Verification is carried out in the estimation calculation, which proves the validity of the method of the present invention and its calculation advantages

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  • Square root UKF calculation method based on standard deviation variable-scale sampling
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  • Square root UKF calculation method based on standard deviation variable-scale sampling

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[0168] Considering the SLAM problem of the robot motion carrier, the carrier motion equation can be given in the Cartesian coordinate system as:

[0169]

[0170] Here the state vector of the SLAM system is x k =[x k ,y k ,φ k ] T , respectively represent the position coordinates and orientation of the carrier at the kth step; V is the carrier speed as the input control quantity, G represents the steering angle of the carrier, the parameter WB represents the wheel base of the carrier, and the noise vector v k is the Gaussian process noise, v k ~N(0,Q k ), where Q k Indicates the noise variance.

[0171] The robot motion carrier is equipped with distance and orientation sensors, which can perceive the target object within a distance of 30m within the range of ±30° in the azimuth angle. From this, the observation equation of the robot SLAM system can be obtained as:

[0172]

[0173] Among them, (r i,x ,r i,y ) is the position coordinate of the landmark perceived...

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Abstract

The invention provides a square root UKF calculation method based on standard deviation variable-scale sampling, and belongs to a system information processing technology in navigation positioning time service in the technical field of robot systems. The method is based on a traditional UKF filter calculation framework; a novel UT transformation sampling point set and a weight coefficient expression thereof are designed according to standard deviation mapped by a deterministic sampling point set in an iterative recursion process, and a weight vector absolute value constructed by a weight coefficient is designed to construct a J-orthogonal transformation calculation strategy, so that the positive definiteness of a weight coefficient vector is ensured. A novel square root UKF filter algorithm based on a standard deviation strategy is designed by utilizing a deterministic sampling point and a weight coefficient set of the deterministic sampling point provided by the invention; the methodis applied to optimal filtering calculation of system state parameters of the autonomous mobile robot, the calculation efficiency problem of a traditional UKF filtering algorithm is effectively solved, so that the robot integrated navigation and positioning service function is achieved.

Description

technical field [0001] The invention relates to the field of robot navigation and positioning, in particular to a square root UKF calculation method based on standard deviation variable-scale sampling. Background technique [0002] Since Julier and Uhlmann proposed the UKF optimal filtering theory and algorithm based on UT transformation in 1995, compared with the extended Kalman optimal filtering algorithm, the UKF algorithm can obtain better numerical calculation results, so the UKF theoretical algorithm has attracted a lot of attention in the academic field. However, the mathematical foundation of the UKF theory and algorithm implementation has not been well proved and theoretically verified. It is only based on a thesis proposed by Julier. In the stochastic control system Approximating the distribution of the probability density function of a random variable using a random approximation strategy is simpler and easier to implement than approximating a nonlinear random fun...

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Application Information

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IPC IPC(8): H03H17/02
CPCH03H17/0223Y02T10/40
Inventor 丁国强田英楠赵朋朋凌丹赵素娜刘娜娄泰山张焕龙王晓雷王妍
Owner ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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