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
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[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...
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