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Inertial navigation system (INS)/wireless sensor network (WSN) indoor mobile robot tight-integration navigation-oriented iterative extended RTS average filtering method

A mobile robot, mean filtering technology, applied in navigation calculation tools and other directions, can solve problems such as incomplete compliance

Active Publication Date: 2013-12-25
SOUTHEAST UNIV
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Problems solved by technology

However, since EKF assumes that the state noise and observation noise of the system are both standard white noise in the filtering process, it does not fully meet the situation in practical applications.

Method used

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  • Inertial navigation system (INS)/wireless sensor network (WSN) indoor mobile robot tight-integration navigation-oriented iterative extended RTS average filtering method
  • Inertial navigation system (INS)/wireless sensor network (WSN) indoor mobile robot tight-integration navigation-oriented iterative extended RTS average filtering method
  • Inertial navigation system (INS)/wireless sensor network (WSN) indoor mobile robot tight-integration navigation-oriented iterative extended RTS average filtering method

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Embodiment Construction

[0039] The present invention will be further explained below in conjunction with the accompanying drawings.

[0040] Such as figure 1 As shown, the iterative extended RTS mean filtering method for tight integrated navigation of INS / WSN indoor mobile robots includes the reference (RS) node part and the unknown (BN) node part. The reference node part is composed of a reference node wireless network receiving module, an ultrasonic ranging module and a time synchronization module. Among them, the reference node wireless network receiving module is mainly responsible for completing the sending and receiving of remote commands. Then turn on the ultrasonic ranging module to measure the corresponding distance information, and finally, return the distance information measured by the ultrasonic ranging module to the unknown node through the reference node wireless network receiving module; the unknown node part is received by the unknown node wireless network Module, INS navigation mod...

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Abstract

The invention discloses an inertial navigation system (INS) / wireless sensor network (WSN) indoor mobile robot tight-integration navigation-oriented iterative extended RTS average filtering method. The method comprises the following steps of through iterative extended kalman filter, carrying out data fusion on navigation information extracted from a local relative coordinate system by INS and WSN, improving a navigation information output period on this basis, carrying out iterative extended RTS smoothing on the data in a small period, then carrying out average filtering, and outputting the data. The iterative extended RTS average filtering method effectively improves a precision of navigation on an indoor mobile robot.

Description

technical field [0001] The invention relates to an iteratively extended RTS mean value filtering method for tight integrated navigation of INS (inertial navigation system) / WSN (wireless sensor network) indoor mobile robot, which 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, making it be entrusted to replace human beings in many occasions to automatically perform certain tasks. High expectations for some routine and dangerous tasks, such as handling robots in logistics and warehousing, production robots in harsh working environments, etc. Robot navigation and positioning, as the key technology to realize robot intelligence and complete autonomy, has gradually become a ...

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Application Information

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IPC IPC(8): G01C21/20
Inventor 陈熙源李庆华徐元高金鹏
Owner SOUTHEAST UNIV
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