Eye movement tracking wheelchair robot control method based on convolutional neural network

The invention relates to the technical field of eye movement wheelchair robots, in particular to an eye movement tracking wheelchair robot control method based on a convolutional neural network. Comprising the steps of identifying an eyeball movement area image through a convolutional neural network model, and obtaining a user preliminary control instruction; performing data serialization on the eyeball motion features processed by the convolutional neural network model to form time sequence data; and inputting the time sequence data into the long-short-term memory neural network, and judging whether to execute the control instruction or not. The convolutional neural network and the long-short-term memory network are connected in series and fused to improve the accuracy and robustness of eye movement data, the eye movement wheelchair robot steering control method and logic design of misoperation detection and diagnosis are achieved, when a user sees left or right, the user possibly wants to steer and possibly