Abstract: In order to solve the step effect and deposition problems in the production of rotating thin-walled parts by additive manufacturing,improve the quality and accuracy of parts manufacturing,and improve the efficiency of additive manufacturing,a multi-axis robot additive manufacturing trajectory optimization based on layer-by-layer generation was proposed. Firstly,the direction vector was constructed based on the inverse geometric model of the six-axis robot,and the direction parameters were extracted from it to define the objective function and constraint function of different layers,and a layer-by-layer trajectory optimization strategy was proposed.Secondly,considering the axis redundancy generated by the coaxial deposition system,the axis redundancy was used to improve the motion trajectory of the robot,and the trajectory optimization was applied to the actual manufacturing of rotating thin-walled parts.Finally,to verify the effectiveness of the proposed method,point-by-point and non-optimized trajectory strategies were selected,and the hollow hemisphere,Laval nozzle and intake funnel configurations were selected for experimental verification.The experimental results show that the proposed method can provide a smoother joint motion trajectory,improve the manufacturing quality and manufacturing efficiency of parts,and compared with the non-optimized trajectory strategy,the proposed method has higher geometric accuracy,which can effectively improve additive manufacturing.

Key words: multi-axis robot, additive manufacturing, multiaxial deposition, trajectory optimization, layer-by-layer generation