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Multi-sensor information fusion method for mobile robot based on UKF (Unscented Kalman Filter)

A mobile robot and multi-sensor technology, applied in the direction of navigation calculation tools, etc., can solve the problem of high calculation accuracy of nonlinear distribution statistics, and achieve the effect of enhanced ability and improved accuracy

Inactive Publication Date: 2013-07-17
JIAMUSI UNIVERSITY
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Problems solved by technology

UKF does not linearize and ignores higher-order terms, so the calculation accuracy of nonlinear distribution statistics is higher

Method used

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  • Multi-sensor information fusion method for mobile robot based on UKF (Unscented Kalman Filter)
  • Multi-sensor information fusion method for mobile robot based on UKF (Unscented Kalman Filter)
  • Multi-sensor information fusion method for mobile robot based on UKF (Unscented Kalman Filter)

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Embodiment Construction

[0014] Below in conjunction with accompanying drawing and specific embodiment, the present invention will be further described, and present embodiment comprises the following steps:

[0015] combine figure 1 In this embodiment, the odometer positioning information and the electronic compass orientation information are filtered in the UKF(A) filtering algorithm to obtain the initial local orientation information L of the robot, and the WLAN positioning information adopts the trilateral positioning method to obtain the preliminary global positioning coordinate W of the robot; W and L are left multiplied by the translation matrix to achieve coordinate translation to obtain the further global orientation information WL of the robot, and use the trilateral positioning method to obtain the positioning information from the RFID positioning information, and use the UKF (B) filtering algorithm to filter the data layer to obtain relatively more accurate The global positioning informatio...

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Abstract

The invention provides a multi-sensor information fusion method for a mobile robot based on a UKF (Unscented Kalman Filter). The method comprises the following processing steps that milemeter locating information and electronic compass azimuth information of the mobile robot are filtered to obtain robot local rough azimuth information L; WLAN (Wireless Local Area Network) locating information is processed by adopting a trilateration locating method to obtain a robot preliminary overall locating coordinate W; the W and the L are subjected to coordinate transformation to obtain overall azimuth information WL; RFID (Radio Frequency Identification) locating information is processed by adopting the trilateration locating method to obtain locating information, and the locating information is subjected to data layer filtering to obtain overall locating information R; the ultrasonic locating information is filtered to obtain barrier local azimuth information Z; and the W, the L, the R and the Z are subjected to total information fusion to obtain robot and barrier overall accurate azimuth information. According to the method, the independent locating accuracy of the mobile robot can be improved significantly, and the anti-interference independent locating capability and the navigation capability of the mobile robot can be improved.

Description

(1) Technical field [0001] The invention belongs to the field of autonomous positioning and navigation of mobile robots, in particular to a multi-sensor information fusion method based on UKF algorithm in multi-sensor autonomous positioning and navigation of mobile robots. (2) Background technology [0002] For mobile robots, the positioning module is an important part of the entire navigation system. In order for the main control module to know the current position and attitude of the robot, measures must be taken to provide sufficiently accurate position and orientation information. Therefore, accurate and reliable positioning technology is a necessary prerequisite for any practical mobile robot. [0003] Multi-sensor information fusion technology is one of the core and basic technologies to improve the autonomous positioning accuracy and navigation performance of mobile robots. This technology is being more and more widely used in specific practices such as intelligent ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
Inventor 姜永成任福君张秀华张连军黄德臣王殿君王斌史庆武王俊发魏天路徐建东谢风伟朱世伟孟庆祥
Owner JIAMUSI UNIVERSITY
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