Technology Recommendations for an Innovative Agricultural Robot Design Based on Technology Knowledge Graphs

Abstract

The process of agricultural robot design is a complex system requiring the cooperation and integration of agricultural, machinery, automation, and information technology. These demands create great challenges for the innovative design of agricultural robots. Meanwhile, more than 95% of the latest inventions and creations in the world are recorded in the patent literature. In order to make effective use of the information and data resources of patents, shorten the design cycle, and provide knowledge for the designers, according to the operation’s objectives, an agricultural robot technology knowledge graph (TKG) was established for innovative designs. By analyzing the patent information, a patent IPC co-classification network (IPCNet) for adaptive design process recognition was put forward to meet the requirements of the different operation objectives and operation links. Through the extraction of the technology keywords and efficacy keywords, based on the word co-occurrence network (WCONet), a technology–efficacy map (TEM) was constructed. Through the integration of the adaptive design process and the TEM, the agricultural robot design TKG was constructed for determining technological recommendations for agricultural robot design. The case of the citrus picking robot design was realized to implement the design process. With the technology recommendation results, the moving system, body, and end-effector for the citrus picking robot were designed to verify the results of the recommendation.