<p>As an intelligent design mode, the human-aided design (HAD) provides a feasible approach for designers to introduce constraints and information elements into optimization algorithms, such as subjective aesthetics or manufacturing limitations, which are difficult to express by formulas. This mode is expected to solve the “retroactive judgment” dilemma faced by engineers, thus improving the acceptance of topology optimization techniques in the engineering field. In order to realize the combination of HAD mode with explicit topology optimization framework, this paper develops a design method, DrawTop, which supports real-time HAD operations based on the topology optimization framework of moving morphable spline components. Inspired by the similarity between hand-drawn lines and spline components, this paper presents a curve reconstruction neural network to directly convert the users’ hand-drawn lines into design variables, and also simplifies the process of adding and deleting components through HAD operations by improving the organization scheme of variable information. Two numerical examples are presented to demonstrate how designers can use DrawTop to improve structural performance by adding hand-drawn details and find local optimal solutions that better align with their design intents. The proposed method endows designers with the ability to interfere in the optimization iteration process, thus achieving the functional expansion of existing topology optimization algorithms.</p>