In order to make industrial sustainable development and build a green and low-carbon industrial system, AGV path planning in a flexible manufacturing workshop has been widely concerned by all walks of life, and more and more scholars are analyzing and researching it. Planning and designing optimal routes for AGVs can not only improve the efficiency of the whole production plant but also enhance the competitive advantage of the whole company for the development of the digital and fully intelligent era. After analyzing the current status of the research on route planning at home and abroad, it is found that very few studies have considered the green energy saving index, and the topic of this chapter is thus generated. Then the path planning is divided into a single AGV system and a multi-AGV system to analyze two parts, respectively, consider the problems that may arise under different circumstances, and put forward optimization algorithms, energy consumption models, and so on. Based on the development background of big data, this chapter carries out an in-depth study and analysis of big data algorithms and energy-saving scheduling problems, and at the same time carries out optimization research and exploration of multi-objective scheduling problems. This chapter has made some innovations in the whole scope of cross research.