Max Robotics — Global Service Robot Directory + US Certification

About

Minrui Fei’s research lies at the intersection of robotics, neural computation, and multi-agent systems, with a focus on making robots smarter, faster, and more collaborative. His most influential work introduces a rapid spiking neural network (SNN) for hand gesture recognition, achieving 76 citations by demonstrating how third-generation neural networks can enable low-power, high-speed robotic perception. Fei has also advanced motion planning for robot manipulators, using improved NSGA-II and reinforcement learning to mimic human arm motion features—work that has garnered 29 and 23 citations, respectively. In multi-robot systems, he tackles formation control and collision avoidance for heterogeneous agents, with his cross-dimensional formation control paper earning 24 citations. Beyond these core contributions, Fei’s early work on ART2 neural networks interacting with environments and his edited volume on Intelligent Computing and the Internet of Things reflect a sustained commitment to bridging computational intelligence with real-world robotic applications. With a citation footprint spanning over 175 total citations, Fei’s research is shaping how robots learn, move, and coordinate—paving the way for more autonomous, efficient, and human-like robotic systems.