A multi-natural sensing parameter fusion processing method for intelligent environment carrying robot to identify floors

A parameter fusion and intelligent environment technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve frequent errors and other problems, achieve prediction model stability, high universality, and improve global search capabilities Effect

Active Publication Date: 2018-07-10
CENT SOUTH UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Directly using air pressure sensing to identify floors will lead to frequent errors

Method used

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  • A multi-natural sensing parameter fusion processing method for intelligent environment carrying robot to identify floors
  • A multi-natural sensing parameter fusion processing method for intelligent environment carrying robot to identify floors
  • A multi-natural sensing parameter fusion processing method for intelligent environment carrying robot to identify floors

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Embodiment Construction

[0048] Such as figure 1 As shown, a multi-natural sensing parameter fusion processing method for an intelligent environment carrying robot to identify a floor includes the following steps:

[0049] Step 1. Before the robot is put into use, collect the temperature, humidity, and air pressure data of each floor of the building at different times, establish a database, and keep the database updated after the robot is put into use. Take a 10-story building as an example.

[0050] Step 2. Number the floors as Floor 1-Floor 10, and classify the data according to different floors.

[0051] Step 3. Set the hourly interval between two adjacent full points as the time interval, and extract the average values ​​of temperature, humidity, and air pressure on the 10 floors within each hour.

[0052] Step 4. For each single floor, take the mean value of temperature, humidity, and air pressure as the observed value, and take the observed value of each time interval as the sample, then floor...

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Abstract

The invention provides a multi-natural sensing parameter fusion processing method for an intelligent environment-carrying robot to identify a floor, using temperature, humidity, and air pressure sensors with low cost to collect data, establish a database, and use big data for the characteristics of air pressure changing with height Processing technology, using the CPSO-optimized ELMAN neural network model to complete the establishment of the prediction model, realize the adaptive identification of the elevator floor of the carrier robot in various environments, and effectively solve the problem of inaccurate floor identification caused by changes in the air pressure value at the same height in different environments . In addition, the present invention does not need to modify the interior or exterior of the elevator, and has extremely high universality.

Description

technical field [0001] The invention belongs to the field of robot control, and in particular relates to a multi-natural sensing parameter fusion processing method for an intelligent environment carrying robot to identify a floor. Background technique [0002] Carrier robot, as an automatic transportation tool, has broad development prospects. Due to modern complex transportation requirements, delivery robots need to realize multi-floor transportation services. However, how to realize the floor identification of the delivery robot is still a difficult point. [0003] At present, there are two main solutions for carrying robots to identify the floors to which elevators go. One is to install external equipment to realize information interaction recognition, and the other is to allow robots to realize autonomous recognition. In the first case, through the internal transformation of the elevator, the interaction between the elevator and the carrying robot is established, and t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/24G06Q10/04
CPCG06F16/285G06F16/35G06N3/08G06Q10/04G06Q50/08G06F18/23213
Inventor 刘辉李燕飞段超王孝楠
Owner CENT SOUTH UNIV
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