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Indoor-mobile-robot-oriented optical flow field vision/inertial navigation system (INS) combined navigation method

A mobile robot and integrated navigation technology, applied in directions such as road network navigators, can solve problems such as the decline of positioning accuracy

Active Publication Date: 2013-11-27
SOUTHEAST UNIV
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Problems solved by technology

The advantage of inertial navigation is that it does not require external parameters as a reference, and it can provide completely autonomous and complete navigation information (robot's position, speed, and attitude, etc.). The positioning accuracy will gradually decrease

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  • Indoor-mobile-robot-oriented optical flow field vision/inertial navigation system (INS) combined navigation method
  • Indoor-mobile-robot-oriented optical flow field vision/inertial navigation system (INS) combined navigation method
  • Indoor-mobile-robot-oriented optical flow field vision/inertial navigation system (INS) combined navigation method

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[0044] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0045] like figure 1 As shown, a system of optical flow field vision / INS combined navigation method for indoor mobile robots, including a vision camera, an inertial measurement unit (IMU) navigation module and a data processing computer.

[0046] The system equation of the extended Kalman filter takes the eastward and northward velocity and acceleration of the INS at each moment as state variables, and the V obtained by visual measurement at each moment E , V N and the heading angle variation ω measured by INS Z as an observation. The system equation of the filter is shown in formula (13):

[0047]

[0048] in is the system noise, and the observation equation is shown in equation (14):

[0049]

[0050] where υ 3×1 is the observation equation noise, V E,k ,V N,k ,Acc E,k ,Acc N,k respectively represent the eastward velocity, northward velocity, east...

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Abstract

The invention relates to an indoor-mobile-robot-oriented optical flow field vision / inertial navigation system (INS) combined navigation method. Two navigation modes of optical-flow-field-based vision navigation and an INS are adopted; a mobile robot acquires a dynamic video of a vehicle according to a vehicle-mounted camera and acquires video optical flow features from the video; transverse speed (Vx) and longitudinal speed (Vy) of the mobile robot under a carrier coordinate system according to the features; east speed (VE) and north speed (VN) of the robot are calculated according to a course angle measured by the INS; the VE and the VN which are obtained through calculation and course angle variation omega Z which is measured by the INS are jointly input into an extended Kalman filter for data fusion to obtain optimal estimation of east speed, north speed and accelerated speed of the mobile robot, having higher precision compared with that of two navigation modes of optical-flow-field-based navigation and the INS. By the method, precise navigation information can be provided for the mobile robot and the positioning range of the indoor mobile rot is widened.

Description

technical field [0001] An optical flow field vision / INS combined navigation method for indoor mobile robots belongs to the technical field of combined positioning in complex environments. Background technique [0002] In recent years, with the rapid development of computer technology, information technology, communication technology, microelectronics technology and robot technology, the research and application of mobile robot technology has made great progress. The navigation and positioning of indoor robots or moving objects, as the key technology to realize the intelligentization and complete autonomy of the production process, has gradually become a research hotspot in this field. However, in a series of complex indoor environments such as weak external radio signals and strong electromagnetic interference, it has a great impact on the accuracy, real-time performance and robustness of moving target navigation information acquisition. How to effectively integrate the lim...

Claims

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Application Information

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IPC IPC(8): G01C21/28
Inventor 李庆华陈熙源高金鹏徐元
Owner SOUTHEAST UNIV
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