The robotic cell is the main carrier of the smart manufacturing system. Studying the robotic cell scheduling problem plays an important role in improving the production efficiency of the smart manufacturing system. This paper studies the robotic cell hybrid flowshop scheduling problem with batch-processing machines. Firstly, a mathematical optimization model is established for the production characteristics of the robotic cell and batch-processing machines. Then, a differential evolution algorithm is designed to solve it, and the concept of genome encoding is proposed. The genome for solving this problem consists of two chromosomes: the first determines the machine distribution at each stage, and the second determines the processing sequence and the handling sequence of the robot. Furthermore, the differential mutation, crossover, and selection operations are designed. Finally, a numerical experiment is performed, and the result shows that, for the robotic cell scheduling problem with batch-processing machines, the differential evolution algorithm can shorten the makespan and get a better solution.