Papers
10
Total Citations
295
H-Index
7
About
Junfei Li is a prolific researcher whose work bridges bio-inspired intelligence, autonomous robotics, and multi-sensor image fusion. His most impactful contribution to date is a comprehensive review of infrared and visible image fusion technologies (2023), which has garnered an impressive 165 citations, reflecting the field's growing need for robust sensing solutions that overcome the individual limitations of infrared and visible-light imaging systems. Alongside this, Li has established himself as a leading voice in bio-inspired robotics, authoring influential surveys on bio-inspired algorithms for robot path planning and broader intelligent robotics applications, collectively accumulating nearly 60 citations. Li's research extends beyond theoretical surveys into algorithmic innovation. His knowledge-based genetic algorithm for collision-free path planning in complex environments and his feature learning-based bio-inspired neural network for multi-robot rescue operations demonstrate a sustained commitment to practical, real-world robotics challenges. More recently, he has explored swarm robotics through fish-inspired neurodynamic models and advanced human-robot collaboration through a digital twins-driven trust framework. With over 295 total citations across a diverse and growing portfolio, Li's work is shaping the intersection of nature-inspired computation, autonomous systems, and intelligent robotics, making him a valuable reference point for students and researchers in these rapidly evolving fields.
Research Focus
Key Achievements
Top Papers
- 1Infrared and Visible Image Fusion Technology and Application: A Review165 citations · 2023
- 2Bio-inspired intelligence with applications to robotics: a survey33 citations · 2021
- 3A Survey on Robot Path Planning using Bio-inspired Algorithms26 citations · 2019
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