Papers
4
Total Citations
26
H-Index
3
About
Yafeng Jiang is a robotics researcher whose work centers on intelligent control, multi-robot coordination, and bio-inspired algorithms for autonomous navigation. His major contributions lie at the intersection of neural networks and immune system models, developing novel approaches to solve fundamental robotics challenges. Jiang pioneered a camera calibration method using neural networks with tunable activation functions for intelligent spaces (16 citations), and created a self-tuning PID controller based on radial basis function networks for service robot trajectory tracking. His most innovative work involves applying biological immune system principles to robotics—he developed the Secondary Immune Response-based Immune Path Planning Algorithm (SIRIPPA) for online multi-robot path planning in dynamic environments, and a real-time immune planning algorithm incorporating specific immune mechanisms for complex environments. These bio-inspired approaches represent a novel paradigm for addressing the computational complexity of multi-robot coordination. Jiang’s research demonstrates how biological principles can be translated into practical engineering solutions, offering efficient alternatives to traditional path planning methods that struggle with real-time constraints and environmental uncertainty.
Research Focus
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