A lightweight optimal design method for magnetic adhesion module of wall-climbing robot based on surrogate model and DBO algorithm

This research combines simulation technology, a surrogate model, and a dung beetle optimizer (DBO) to propose a structural optimization design method for lightweight adhesive modules. The structure of the wall-climbing robot is introduced, and its adhesion stability is analyzed. Through simulation comparison of four typical Halbach array magnetic circuit modes, it was determined that the adhesion generated by the three-magnetic circuit structure mode is more advantageous. Determine the parameters that need to be optimized through sensitivity analysis. The Chebyshev model of adhesion force and parameters was established. An optimization model aimed at lightweight and the constraints of adhesion stability and structural parameters was set. The penalty function combined with DBO was used to solve the optimization model. Compared with before optimization, the weight of the adhesive module is reduced by 11.7 %. The experiments verified the adhesive module’s adhesion force and the robot’s load capacity.