Unscented Kalman filter (UKF)-based underwater robot state and parameter joint estimation method

An underwater robot and joint estimation technology, applied in underwater operation equipment, transportation and packaging, ships, etc., can solve problems such as propeller failure, achieve simple, high estimation accuracy, and avoid linearization errors

Active Publication Date: 2015-03-11
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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AI Technical Summary

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 underwater robot is not completely invalid. If the efficiency loss factor can be identified in real time , and then redistribute the thrust, the underwater robot may still complete the expected task

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  • Unscented Kalman filter (UKF)-based underwater robot state and parameter joint estimation method
  • Unscented Kalman filter (UKF)-based underwater robot state and parameter joint estimation method
  • Unscented Kalman filter (UKF)-based underwater robot state and parameter joint estimation method

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Embodiment Construction

[0030] The solution of the present invention will be further described in detail below in conjunction with the drawings and embodiments:

[0031] See attached figure 1 , Is a schematic diagram of the method of the present invention. The UKF-based joint estimation method of the state and parameters of the underwater robot includes the following steps: establish an offline extended reference model of the underwater robot; according to the online pose information detected by the pose sensor k , Using the UKF filter estimation algorithm, combined with the offline extended reference model of the underwater robot as the extended system state equation, transfer and update the extended state composed of the system state and thruster failure, and estimate the state and parameter information of the system in real time. Result value estimated by the system And P k ; Here the state information of the system includes filtered pose information q k And real-time estimated speed information Th...

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Abstract

The invention discloses an unscented Kalman filter (UKF)-based underwater robot state and parameter joint estimation method. According to the method, expansion reference models of an underwater robot are established, and comprise a kinetic model of the underwater robot and a fault model of a propeller. According to pose information detected by a position sensor, the expansion reference models are subjected to on-line joint estimation through states of the underwater robot, including pose and speed, and propeller fault parameters by a UKF algorithm, and the speed information of the underwater robot and the propeller fault information are estimated in real time. The method has a high real-time property, and the states and parameters of a system can be subjected to joint estimation; and under the condition that prior information of process noise and measurement noise is known, high estimation accuracy can be achieved by the method.

Description

Technical field [0001] The invention relates to a joint estimation method of the state and parameters of an underwater robot based on the Unscented Kalman Filter (UKF), in particular to a joint estimation method of the state and thruster fault parameters of an underwater robot based on the UKF. 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 action means are getting higher and higher. Since underwater robots can observe, photograph, salvage and construction operations underwater, they are widely used in marine development. With the continuous development and maturity of underwater robot technology, its missions are becoming more and more complicated. In many cases, the environment of underwater robots mainly includes their own behavior environment, external natural environment, target environment, etc., which are complex and un...

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Application Information

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Patent Type & Authority Patents(China)
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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