Underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF)

An underwater robot and joint estimation technology, which can be used in underwater operation equipment, transportation and packaging, ships, etc., and can solve problems such as thruster failure.

Active Publication Date: 2013-01-09
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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Problems solved by technology

Traditional pre-programmed underwater robots generally take measures such as dumping and floating when detecting a fault in the propeller. In fact, in many cases, the propeller of the underwa

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  • Underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF)
  • Underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF)
  • Underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF)

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[0040] Below in conjunction with accompanying drawing and embodiment the scheme of the present invention is described in further detail:

[0041] See attached Figure 1~2 , is the realization principle diagram of the method of the present invention and its filter estimation flow chart. A method for jointly estimating the state and parameters of an underwater robot based on adaptive UKF is characterized in that it comprises the following steps:

[0042] On the basis of the underwater robot dynamics model, the thruster fault is modeled to obtain an offline extended reference model; according to the online pose information y detected by the pose sensor k , using the main filter of the adaptive UKF as the standard UKF filter estimation algorithm, combined with the offline extended reference model of the underwater robot as the extended system state equation, the extended state transfer and update of the system state and thruster fault composition, and real-time estimation Get th...

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Abstract

The invention discloses an underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF). The method comprises building an expanding reference model of an underwater robot, and enabling the reference model to have a dynamical model of the underwater robot and a fault model of a thruster; adopting a main filter of the self-adaption UKF to deliver and update expanding states composed of poses and speed of the underwater robot state and faults of the thruster according to pose information detected by a position sensor, and timely estimating speed information of the underwater robot and fault message of the thruster; and simultaneously adopting an accessory filter of the self-adaption UKF to timely estimate noise information of a system according to innovation information of the main filter. The underwater robot state and parameter joint estimation method has good instantaneity, can conduct joint estimation on states and parameters of the system, and can achieve high estimation accuracy when priori information of process noise and measurement noise is unknown.

Description

technical field [0001] The present invention relates to a method for jointly estimating the state and parameters of an underwater robot based on an adaptive unscented Kalman filter (UKF, Unscented Kalman Filter), in particular to a joint estimation method for the state of an underwater robot and propeller failure parameters based on an adaptive UKF Estimation method. technical background [0002] With the rapid development of marine development, there are more and more underwater construction and construction projects, and the performance requirements for underwater means of action are also getting higher and higher. Because underwater robots can perform observation, photography, salvage and construction operations underwater, they are widely used in ocean development. The health of the propeller determines whether the underwater robot can complete the expected tasks well. Traditional pre-programmed underwater robots generally take measures such as dumping and floating whe...

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Application Information

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IPC IPC(8): B63C11/52
Inventor 刘开周程大军李一平封锡盛
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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