Neural network and swarm hybrid calculation method for intelligent environment carrier robot floor identification

A neural network and intelligent environment technology, applied in the field of neural network group hybrid computing, can solve the problems of not considering the oscillation of the output signal of the air pressure sensor and the change of the reading in the cycle, potential safety hazards, and the inability to obtain the correct position information of the elevator car, etc., to achieve Improve precision, improve accuracy, improve the effect of shock

Active Publication Date: 2017-11-24
CENT SOUTH UNIV
View PDF1 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the readings of the air pressure sensor vary with the weather and altitude, and the readings are fluctuating. Relying on the air pressure sensor alone to detect the floor will produce a large error. The above-mentioned patent does not consider the oscillation of the output sig

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Neural network and swarm hybrid calculation method for intelligent environment carrier robot floor identification
  • Neural network and swarm hybrid calculation method for intelligent environment carrier robot floor identification
  • Neural network and swarm hybrid calculation method for intelligent environment carrier robot floor identification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0052] Such as figure 1 As shown, a neural network group hybrid computing method for carrying robots in an intelligent environment to identify floors, including the following steps:

[0053] 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 updating the database after the robot is put into use, taking a 10-story building as an example.

[0054] Step 2. Number the floors as Floor 1-Floor 10, and classify the data according to different floors.

[0055] 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.

[0056] Step 4. For each single floor, take the average value of temperature, h...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a neural network and swarm hybrid calculation method for intelligent environment carrier robot floor identification. After various acquired data are clustered according to weather modes, based on different weather modes, fluctuating pressure sensor readings are subjected to FIR filtering processing, the readings are then transmitted to a data analysis module for neural network learning, and the accuracy and the real-time performance of floor identification are greatly improved. The vibration problem of data acquired by a pressure sensor can be greatly improved, and the height data signal analysis precision is greatly improved; universal adaptability is realized, and the method can handle elevator floor identification under each altitude, each geographical location and each weather condition; and the method is not limited to be used by the carrier robot in the elevator, floor estimation in a passageway can also be carried out, and the method can also be applied to fields such as overhead operation and unmanned aerial vehicles.

Description

technical field [0001] The invention belongs to the field of robot control, in particular to a neural network group mixing calculation method for an intelligent environment carrying robot to identify floors. Background technique [0002] At present, the way for the elevator control system to obtain the floor number of the floor where the elevator is currently located is: to install the induction element on the base station floor of the elevator, and to install the induction receiver on the position corresponding to the induction element on the car of the elevator; , through the interaction between the sensing element and the sensing receiver, the fact that the elevator is at the base floor is known, so that the current floor number of the elevator is set as the floor number of the base station floor (the floor number system of the base station floor is known in advance); When going up or down, the floor number of the floor where the elevator car is located is calculated by a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06N3/08G06N3/00
CPCG06N3/006G06N3/008G06N3/08
Inventor 刘辉李燕飞黄家豪王孝楠段超
Owner CENT SOUTH UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap