Yilin Yang

Papers

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About

Yilin Yang has made significant contributions to the field of autonomous robotics, with a particular focus on intelligent navigation and behavior modeling. Their research centers on applying Petri nets—a powerful mathematical modeling tool—to enhance robot decision-making and control systems. Yang’s most cited work, “A self-navigating robot using Fuzzy Petri nets” (2017, 19 citations), demonstrates a novel integration of fuzzy logic with Petri net structures, enabling robots to navigate complex, dynamic environments without pre-mapped routes. This approach reduces the computational overhead and standby time typically associated with traditional environment mapping. In related studies, Yang analyzed soccer robot behaviors using Time Petri nets (2016, 10 citations) and developed efficient obstacle avoidance strategies for mobile robots (2016, 6 citations), further advancing the practical application of Petri nets in robotics. By combining formal modeling techniques with adaptive control, Yang has created frameworks that improve both the transparency and efficiency of autonomous systems. Their work offers valuable insights for researchers in robotics, control theory, and artificial intelligence, particularly those interested in developing more intuitive and resource-efficient navigation algorithms.