Shujuan Yi

Heilongjiang Bayi Agricultural University

Papers

Total Citations

H-Index

About

Shujuan Yi is a leading researcher in biomimetic robotics and intelligent control systems, with a particular focus on bio-inspired path planning and deep learning integration. Her most cited work, "A novel path planning method for biomimetic robot based on deep learning" (2016, 21 citations), introduced an innovative approach that leverages multi-layer convolutional neural networks (CNNs) to address complex navigation challenges in biomimetic robots. By employing sparse autoencoder training algorithms to generate convolution kernels of varying scales, Yi’s method significantly enhances a robot’s ability to perceive and adapt to dynamic environments. This contribution bridges the gap between biological locomotion principles and advanced artificial intelligence, offering a robust framework for autonomous decision-making in unstructured terrains. Her research has been instrumental in advancing the fields of intelligent robotics and neural network-based control, with implications for search-and-rescue operations, environmental monitoring, and autonomous exploration. Yi’s work continues to inspire new generations of researchers seeking to merge biological inspiration with cutting-edge computational techniques, solidifying her reputation as a key innovator in biomimetic systems and deep learning applications.