Xinwei Cao
Shanghai University, Swansea University, Jiangnan University
Papers
11
Total Citations
491
H-Index
9
About
Xinwei Cao is a prominent researcher specializing in intelligent robotics, bio-inspired computational methods, and cooperative autonomous systems. His work sits at the intersection of neural networks, evolutionary algorithms, and robotic control, with a particular focus on developing smart, adaptive frameworks for real-world robotic applications. Cao's most influential contribution is his pioneering application of the Beetle Antennae Search (BAS) algorithm — a bio-inspired optimization technique modeled on beetles' olfactory foraging behavior — to robotic control challenges. His 2020 paper establishing a cooperative robot control framework for smart home environments has garnered 125 citations, while subsequent work applying BAS to human-guided cooperative robots and redundant manipulator tracking control has collectively attracted hundreds of citations, underscoring the breadth of his impact. Beyond bio-inspired methods, Cao has made significant advances in zeroing neural dynamics for inter-robot management and time-dependent nonlinear optimization, and has explored the transformative potential of blockchain technology in distributed robotic systems. His research consistently bridges theoretical innovation with practical application, spanning biped locomotion, surgical robotics, and multi-robot coordination. With over 400 cumulative citations across his published works, Cao has established himself as a distinctive voice in intelligent robotics research, offering novel computational tools that make autonomous systems more robust, adaptable, and collaborative.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10