A robot autonomous positioning method based on convolutional neural network fusion of imu and wifi information

Abstract

The invention discloses a robot autonomous positioning method based on convolutional neural network fusion of IMU and WiFi information. The method adopts a two-channel convolutional neural network. The steps include: taking the information of WiFi and IMU as the input of two channels respectively, Features are extracted through convolution, and then the importance of the two channels is automatically obtained through the SE module, weight feature matching is performed, and the final output is obtained through the fully connected layer and the softmax function; the serial number corresponding to the reference point is used as the output of the network, and the network to train. In the positioning stage, the WiFi and IMU information of the point to be measured is input into the trained network, and the position of the positioning point is estimated by using the reference point coordinates corresponding to the serial number output by the output layer and the probability corresponding to the serial number. The method of the present invention can effectively avoid errors caused by RSSI data easy to fluctuate in traditional WiFi positioning and the second integral of acceleration in IMU positioning, and can obtain the position of the robot simply and efficiently in the positioning stage.

Description

technical field [0001] The invention relates to the field of robot positioning, in particular to the fusion of an inertial measurement unit (InertialMeasurement Unit, IMU) and a two-channel convolutional neural network embedded in an excitation (Squeeze-and-Excitation, SE) module for WiFi positioning to obtain a robot position method research. Background technique [0002] Robot positioning technology is the most basic link to realize autonomous positioning and navigation. It is the position of the robot relative to the global coordinate system and its own attitude in the two-dimensional working environment. At present, positioning technology can be divided into absolute positioning and relative positioning. The purpose of absolute positioning is to obtain the position of the positioning target in the global coordinate system, such as WiFi positioning. Relative positioning needs to know the position and attitude of the positioning target at the initial moment, and then comb...

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Problems solved by technology

[0006] Aiming at the problem that the accuracy of WiFi positioning is easily affected by the environment and the single placement angle of the receiving device, the IMU positioning has cumulative errors, and the positioning accuracy is poor for a long time, the present invention proposes to use a two-channel convolutional neural network (Squeeze-and- Excitation Two channels Convolutional Neural Network, SETCNN) integrates the information of WiFi and IMU to perform robot positioning. The network structure is as attached figure 1 shown

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