In view of the environment recognition problems for bionic robot fish working near the target

a near wall flow recognition method based on artificial lateral line (ALL) is proposed in this paper. Firstly

the feasibility of near wall flow field environment recognition by means of ALL was analyzed theoretically. Then

the ALL virtual pressure sensor array was established. The surface pressure data of bionic robot fish were calculated and extracted under different parameters (inflow velocity v

near wall distance d

and swimming frequency f) by using computational fluid dynamics (CFD) method. Finally

the regression model of inflow velocity and near wall distance based on multilayer feed forward neural network was established

and the model structure and data characteristics were optimized. Results show that the wall effect caused asymmetric distribution flow around the fish. The lateral sensors at the head and tail of the fish had high identification for flow field parameters. Eliminating the weak correlation features had little effect on the prediction indexes of inflow velocity and near wall distance

and was helpful to reduce the complexity of the prediction model. The results can provide theoretical and methodological basis for information extraction and processing of underwater robot environment recognition.