A Human Target Tracking Method Based on Progressive Unscented Kalman Filter

An unscented Kalman, human body target technology, applied in the field of mobile robots, can solve the problems of poor stability and low accuracy, and achieve the effect of reducing linearization error, improving tracking accuracy, and ensuring computational complexity

Active Publication Date: 2021-02-26
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the deficiencies of low accuracy and poor stability of the existing human target tracking method, the present invention provides a human target tracking method based on progressive unscented Kalman filter. Under the premise of ensuring computational complexity, the method can Considering the impact of linearization error on the system, effectively improving the tracking accuracy of human targets

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  • A Human Target Tracking Method Based on Progressive Unscented Kalman Filter
  • A Human Target Tracking Method Based on Progressive Unscented Kalman Filter
  • A Human Target Tracking Method Based on Progressive Unscented Kalman Filter

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Embodiment Construction

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] refer to Figure 1 ~ Figure 3 , a human target tracking method based on progressive unscented Kalman filter, by figure 1 As shown in , the following robot uses a laser sensor to detect the human target, and obtains the distance and angle between the service robot and the human target; figure 2 As shown, according to the measurement information returned by the laser sensor, the positional relationship between the robot and the human target in the global coordinates is obtained through coordinate conversion. The state space model of the follower system is shown in formula (1), and the sensor measurement model is shown in formula ( 2) as shown:

[0022]

[0023]

[0024]

[0025]

[0026] Among them, the state vector of the system is and are the positions of the human target on the x-axis and y-axis at time k, respectively, and is the vel...

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Abstract

A human target tracking method based on progressive unscented Kalman filtering. This method is aimed at the problem of system tracking performance degradation caused by excessive linearization error. During the measurement update process, the current measurement information is gradually introduced to reduce linearity. It can effectively improve the tracking accuracy of human targets. Secondly, a judgment condition is introduced in the measurement asymptotic process to further compensate the linearization error existing in the system. Compared with the existing target tracking methods, the method fully considers the influence of linearization error on the system, and improves the tracking accuracy of human targets on the premise of ensuring the computational complexity.

Description

technical field [0001] The invention belongs to the field of mobile robots, in particular to a human body target tracking method for following a robot. Background technique [0002] With the increasing requirements of social production and life, the mobile robot industry has developed very rapidly and gradually penetrated into the fields of social services, medical health and resource detection. In an unknown and complex dynamic environment, realizing the identification and tracking of service objects is one of the main ways to improve the environmental adaptability of mobile robots, and it is also the premise and basis for completing complex specified tasks through human-computer cooperation. [0003] In order to realize the effective detection and tracking of human targets by mobile robots, it is necessary to design a stable and good performance human target tracking estimator. Considering the nonlinear filtering problem in the process of human target tracking, some commo...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20G01S17/66
CPCG01C21/20G01S17/66
Inventor 俞立郑婷婷杨旭升赵礼艳
Owner ZHEJIANG UNIV OF TECH
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