To obtain the satisfaction of the user's various needs through the analysis and research on the behavior of the user using the sweeping robot in the home situation,, so as to formulate the interactive experience optimization strategy of the sweeping robot and improve the user's APP interactive experience. First, based on methods such as desktop research, cleaning behavior observation, etc., the existing functions of the household sweeping robot APP and the potential user requirements were obtained, and the function set was prioritized through the KANO model; then, the higher priority of the existing functions was performed Usability level test, and conduct contextual interaction behavior analysis for functions with insufficient usability, and explore specific issued affecting the interactive experience in the existing functions of the sweeping robot APP. So as to form an interactive experience optimization strategy and verify its effectiveness through design practice cases. The availability factor of the optimized sweeping robot APP had been improved to varying degrees, which proved the effectiveness of the method. This method can help developers to scientifically, efficiently and accurately select product function optimization objects, and systematically obtain users' shortcomings in the interaction with the sweeping robot, assisting the iterative design of sweeping robot interaction, and improving user experience.